{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# source file\n",
    "with open('main.bib', 'r') as file:\n",
    "    data = file.read()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'@article{virgili2007optical,\\n  title={Optical coherence tomography versus stereoscopic fundus photography or biomicroscopy for diagnosing diabetic macular edema: a systematic review},\\n  author={Virgili, Gianni and Menchini, Francesca and Dimastrogiovanni, Andrea F and Rapizzi, Emilio and Menchini, Ugo and Bandello, Francesco and Chiodini, Raffaella Gortana},\\n  journal={Investigative ophthalmology \\\\& visual science},\\n  volume={48},\\n  number={11},\\n  pages={4963--4973},\\n  year={2007},\\n  publisher={The Association for Research in Vision and Ophthalmology}\\n}\\n@article{davis2008comparison,\\n  title={Comparison of time-domain OCT and fundus photographic assessments of retinal thickening in eyes with diabetic macular edema},\\n  author={Davis, Matthew D and Bressler, Susan B and Aiello, Lloyd Paul and Bressler, Neil M and Browning, David J and Flaxel, Christina J and Fong, Donald S and Foster, William J and Glassman, Adam R and Hartnett, Mary Elizabeth R and others},\\n  journal={Investigative ophthalmology \\\\& visual science},\\n  volume={49},\\n  number={5},\\n  pages={1745--1752},\\n  year={2008},\\n  publisher={The Association for Research in Vision and Ophthalmology}\\n}\\n@article{alhadeff2017association,\\n  title={The association between clinical features seen on fundus photographs and glaucomatous damage detected on visual fields and optical coherence tomography scans},\\n  author={Alhadeff, Paula A and De Moraes, C Gustavo and Chen, Monica and Raza, Ali S and Ritch, Robert and Hood, Donald C},\\n  journal={Journal of glaucoma},\\n  volume={26},\\n  number={5},\\n  pages={498},\\n  year={2017},\\n  publisher={NIH Public Access}\\n}\\n@article{gregori2013measuring,\\n  title={Measuring drusen over time: OCT vs. Fundus Photography},\\n  author={Gregori, Giovanni and Garcia Filho, Carlos Alexandre and Yehoshua, Zohar and Nunes, Renata Portella and Feuer, William and Sadda, Srinivas and Rosenfeld, Philip},\\n  journal={Investigative Ophthalmology \\\\& Visual Science},\\n  volume={54},\\n  number={15},\\n  pages={5839--5839},\\n  year={2013},\\n  publisher={The Association for Research in Vision and Ophthalmology}\\n}\\n@article{jain2010quantitative,\\n  title={Quantitative comparison of drusen segmented on SD-OCT versus drusen delineated on color fundus photographs},\\n  author={Jain, Nieraj and Farsiu, Sina and Khanifar, Aziz A and Bearelly, Srilaxmi and Smith, R Theodore and Izatt, Joseph A and Toth, Cynthia A},\\n  journal={Investigative ophthalmology \\\\& visual science},\\n  volume={51},\\n  number={10},\\n  pages={4875--4883},\\n  year={2010},\\n  publisher={The Association for Research in Vision and Ophthalmology}\\n}\\n@article{morgan2016fundus,\\n  title={The fundus photo has met its match: optical coherence tomography and adaptive optics ophthalmoscopy are here to stay},\\n  author={Morgan, Jessica IW},\\n  journal={Ophthalmic and Physiological Optics},\\n  volume={36},\\n  number={3},\\n  pages={218--239},\\n  year={2016},\\n  publisher={Wiley Online Library}\\n}\\n%\\\\RequirePackage{filecontents}\\n%\\\\begin{filecontents*}{\\\\file.bib}\\n@article{whitcher2001corneal,\\n  title={Corneal blindness: a global perspective},\\n  author={Whitcher, J P and Srinivasan, M and Upadhyay, M P},\\n  journal={Bulletin of the World Health Organization},\\n  volume={79},\\n  pages={214--221},\\n  year={2001},\\n  publisher={SciELO Public Health}\\n}\\n@article{costagliola2009pharmacotherapy,\\n  title={Pharmacotherapy of intraocular pressure: part I. Parasympathomimetic, sympathomimetic and sympatholytics},\\n  author={Costagliola, C and Dell\\'Omo, R and Romano, M R and Rinaldi, M and Zeppa, L and Parmeggiani, F},\\n  journal={Expert Opinion on Pharmacotherapy},\\n  volume={10},\\n  number={16},\\n  pages={2663--2677},\\n  year={2009},\\n  publisher={Taylor \\\\& Francis}\\n}\\n@article{krolewski1986risk,\\n  title={Risk of proliferative diabetic retinopathy in juvenile-onset type I diabetes: a 40-yr follow-up study},\\n  author={Krolewski, AS and Warram, JH and Rand, LI and Christlieb, AR and Busick, EJ and Kahn, CR},\\n  journal={Diabetes Care},\\n  volume={9},\\n  number={5},\\n  pages={443--452},\\n  year={1986},\\n  publisher={Am Diabetes Assoc}\\n}\\n@article{nicolela2016optic,\\n  title={Optic {N}erve: {C}linical {E}xamination, in {P}earls of {G}laucoma {M}anagement. {S}pringer, {B}erlin, {H}eidelberg},\\n  author={Nicolela, MT and Vianna, JR},\\n  booktitle={Pearls of Glaucoma Management},\\n  pages={17-26},\\n  year={2016},\\n  publisher={Springer}\\n}\\n@inbook{leopold_2017,\\n    Author = {Leopold, H.A. and Zelek, J.S. and Lakshminarayanan, V.},\\n    Booktitle = {Biomedical signal processing in big data.},\\n    Chapter = {Deep Learning Methods for Retinal Image Analysis in Signal Processing and Machine Learning for Biomedical Big Data. eds. Sejdi\\\\\\'{c}, E and Falk, TH.},\\n    Publisher = {CRC Press},\\n    pages = {329-365},\\n    Year = {2018}\\n}\\n@book{sejdic2018signal,\\n  title={Signal Processing and Machine Learning for Biomedical Big Data},\\n  author={Sejdic, E and Falk, TH},\\n  year={2018},\\n  publisher={CRC Press}\\n}\\n@article{jager2008age,\\n  title={Age-related macular degeneration},\\n  author={Jager, RD and Mieler, WF and Miller, JW},\\n  journal={New England Journal of Medicine},\\n  volume={358},\\n  number={24},\\n  pages={2606--2617},\\n  year={2008},\\n  publisher={Mass Medical Soc}\\n}\\n@article{friedman2004prevalence,\\n  title={Prevalence of age-related macular degeneration in the United States},\\n  author={Friedman, David S and O’Colmain, Benita J and Munoz, Beatriz and Mitchell, Paul and Kempen, John and others},\\n  journal={Arch Ophthalmol},\\n  volume={122},\\n  number={4},\\n  pages={564--572},\\n  year={2004}\\n}\\n@article{najafabadi2015deep,\\n  title={Deep learning applications and challenges in big data analytics},\\n  author={Najafabadi, MM and Villanustre, F and Khoshgoftaar, TM and Seliya, N and Wald, R and Muharemagic, E},\\n  journal={Journal of Big Data},\\n  volume={2},\\n  number={1},\\n  pages={1},\\n  year={2015},\\n  publisher={Springer}\\n}\\n@article{chong2017deep,\\n  title={Deep learning networks for stock market analysis and prediction: Methodology, data representations, and case studies},\\n  author={Chong, E and Han, C and Park, FC},\\n  journal={Expert Systems with Applications},\\n  volume={83},\\n  pages={187--205},\\n  year={2017},\\n  publisher={Elsevier}\\n}\\n@article{litjens2017survey,\\n  title={A survey on deep learning in medical image analysis},\\n  author={Litjens, G and Kooi, T and Bejnordi, BE and Setio, AAA and Ciompi, F and Ghafoorian, M and Van Der Laak, JA and Van Ginneken, B and S{\\\\\\'a}nchez, CI},\\n  journal={Medical image analysis},\\n  volume={42},\\n  pages={60--88},\\n  year={2017},\\n  publisher={Elsevier}\\n}\\n@inproceedings{krizhevsky2012imagenet,\\n  title={Imagenet classification with deep convolutional neural networks},\\n  author={Krizhevsky, A and Sutskever, I and Hinton, GE},\\n  booktitle={Advances in neural information processing systems},\\n  pages={1097--1105},\\n  year={2012}\\n}\\n@inproceedings{zeiler2014visualizing,\\n  title={Visualizing and understanding convolutional networks},\\n  author={Zeiler, MD and Fergus, R},\\n  booktitle={European Conference on Computer Vision eds. Fleet D., Pajdla T., Schiele B., Tuytelaars T.},\\n  volume={8689},\\n  pages={818--833},\\n  year={2014},\\n  organization={Springer}\\n}\\n@article{simonyan2014very,\\n  title={Very deep convolutional networks for large-scale image recognition},\\n  author={Simonyan, K and Zisserman, A},\\n  journal={arXiv preprint arXiv:1409.1556},\\n  year={2014}\\n}\\n@inproceedings{szegedy2015going,\\n  title={Going deeper with convolutions},\\n  author={Szegedy, C and Liu, W and Jia, Y and Sermanet, P and Reed, S and Anguelov, D and Erhan, D and Vanhoucke, V and Rabinovich, A},\\n  booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition},\\n  pages={1--9},\\n  year={2015}\\n}\\n@inproceedings{he2016deep,\\n  title={Deep residual learning for image recognition},\\n  author={He, K and Zhang, X and Ren, S and Sun, J},\\n  booktitle={The IEEE Conference on Computer Vision and Pattern Recognition},\\n  pages={770--778},\\n  year={2016}\\n}\\n@inproceedings{girshick2014rich,\\n  title={Rich feature hierarchies for accurate object detection and semantic segmentation},\\n  author={Girshick, R and Donahue, J and Darrell, T and Malik, J},\\n  booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition},\\n  pages={580--587},\\n  year={2014}\\n}\\n@inproceedings{ren2015faster,\\n  title={Faster r-cnn: Towards real-time object detection with region proposal networks},\\n  author={Ren, S and He, K and Girshick, R and Sun, J},\\n  booktitle={Advances in Neural Information Processing Systems},\\n  pages={91--99},\\n  year={2015}\\n}\\n@article{yannuzzi2004ophthalmic,\\n  title={Ophthalmic fundus imaging: today and beyond},\\n  author={Yannuzzi, LA and Ober, MD and Slakter, JS and Spaide, RF and Fisher, YL and Flower, RW and Rosen, R},\\n  journal={American Journal of Ophthalmology},\\n  volume={137},\\n  number={3},\\n  pages={511--524},\\n  year={2004},\\n  publisher={Elsevier}\\n}\\n@article{huang1991optical,\\n  title={Optical coherence tomography},\\n  author={Huang, D and Swanson, EA and Lin, CP and Schuman, JS and Stinson, WG and Chang, W and Hee, MR and Flotte, T and Gregory, K and Puliafito, CA and others},\\n  journal={Science},\\n  volume={254},\\n  number={5035},\\n  pages={1178--1181},\\n  year={1991},\\n  publisher={American Association for the Advancement of Science}\\n}\\n@mastersthesis{roy2018automated,\\n  title={Automated Segmentation of Retinal Optical Coherence Tomography Images},\\n  author={Roy, P},\\n  year={2018},\\n  school={University of Waterloo}\\n}\\n@article{staal2004ridge,\\n  title={Ridge-based vessel segmentation in color images of the retina},\\n  author={Staal, J and Abr{\\\\`a}moff, MD and Niemeijer, M and Viergever, MA and Van Ginneken, B},\\n  journal={IEEE Transactions on Medical Imaging},\\n  volume={23},\\n  number={4},\\n  pages={501--509},\\n  year={2004},\\n  publisher={IEEE}\\n}\\n@article{budai2013robust,\\n  title={Robust vessel segmentation in fundus images},\\n  author={Budai, A and Bock, R and Maier, A and Hornegger, J and Michelson, G},\\n  journal={International Journal of Biomedical Imaging, vol. 2013,ID 154860 pages 11},\\n  year={2013},\\n  publisher={Hindawi}\\n}\\n@article{hoover2000locating,\\n  title={Locating blood vessels in retinal images by piecewise threshold probing of a matched filter response},\\n  author={Hoover, AD and Ko, Va and Goldbaum, M},\\n  journal={IEEE {T}ransactions on {M}edical {I}maging},\\n  volume={19},\\n  number={3},\\n  pages={203--210},\\n  year={2000},\\n  publisher={IEEE}\\n}\\n@article{hoover2003locating,\\n  title={Locating the optic nerve in a retinal image using the fuzzy convergence of the blood vessels},\\n  author={Hoover, A and Goldbaum, M},\\n  journal={IEEE Transactions on Medical Imaging},\\n  volume={22},\\n  number={8},\\n  pages={951--958},\\n  year={2003},\\n  publisher={IEEE}\\n}\\n@article{niemeijer2010retinopathy,\\n  title={Retinopathy online challenge: automatic detection of microaneurysms in digital color fundus photographs},\\n  author={Niemeijer, M and Van G, B and Cree, M and Mizutani, A and Quellec, G and S{\\\\\\'a}nchez, CI and Zhang, B and Hornero, R and Lamard, M and Muramatsu, C and others},\\n  journal={IEEE Transactions on Medical Imaging},\\n  volume={29},\\n  number={1},\\n  pages={185--195},\\n  year={2010},\\n  publisher={Institute of Electrical and Electronics Engineers, Inc., 345 E. 47 th St. NY NY 10017-2394 USA}\\n}\\n@inproceedings{zhang2010origa,\\n  title={Origa-light: An online retinal fundus image database for glaucoma analysis and research},\\n  author={Zhang, Z and Yin, FS and Liu, J and Wong, WK and Tan, NM and Lee, BH and Cheng, J and Wong, TY},\\n  booktitle={Engineering in Medicine and Biology Society (EMBC), 2010 Annual International Conference of the IEEE},\\n  pages={3065--3068},\\n  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National Eye Institute Visual Function Questionnaire in the Age-Related Eye Disease Study (AREDS)},\\n  author={Clemons, TE and Chew, EY and Bressler, SB and McBee, W},\\n  journal={Arch Ophthalmology},\\n  volume={121},\\n  number={2},\\n  pages={211--7},\\n  year={2003}\\n}\\n@inproceedings{zhang2013achiko,\\n  title={ACHIKO-K: Database of fundus images from glaucoma patients},\\n  author={Zhang, Z and Liu, J and Yin, F and Lee, B and Wong, DW and Sung, KR},\\n  booktitle={2013 IEEE 8th Conference on Industrial Electronics and Applications (ICIEA)},\\n  pages={228--231},\\n  year={2013}\\n}\\n@inproceedings{fumero2011rim,\\n  title={RIM-ONE: An open retinal image database for optic nerve evaluation},\\n  author={Fumero, F and Alay{\\\\\\'o}n, S and Sanchez, JL and Sigut, J and Gonzalez-Hernandez, M},\\n  booktitle={2011 24th International Symposium on Computer-based Medical Systems (CBMS)},\\n  pages={1-6},\\n  year={2011}\\n}\\n@article{sivaswamy2015comprehensive,\\n  title={A comprehensive retinal image dataset for the assessment of glaucoma from the optic nerve head analysis},\\n  author={Sivaswamy, J and Krishnadas, S and Chakravarty, A and Joshi, GD and Tabish, AS and others},\\n  journal={JSM Biomedical Imaging Data Papers},\\n  volume={2},\\n  number={1},\\n  pages={1004},\\n  year={2015}\\n}\\n@inproceedings{sivaswamy2014drishti,\\n  title={Drishti-gs: Retinal image dataset for optic nerve head (onh) segmentation},\\n  author={Sivaswamy, J and Krishnadas, SR and Joshi, GD and Jain, M and Tabish, AUS},\\n  booktitle={2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI)},\\n  pages={53--56},\\n  year={2014}\\n}\\n@article{carmona2008identification,\\n  title={Identification of the optic nerve head with genetic algorithms},\\n  author={Carmona, EJ and Rinc{\\\\\\'o}n, M and Garc{\\\\\\'\\\\i}a-Feijo{\\\\\\'o}, J and Mart{\\\\\\'\\\\i}nez-de-la-Casa, JM},\\n  journal={Artificial Intelligence in Medicine},\\n  volume={43},\\n  number={3},\\n  pages={243--259},\\n  year={2008},\\n  publisher={Elsevier}\\n}\\n@article{decenciere2013teleophta,\\n  title={TeleOphta: Machine learning and image processing methods for teleophthalmology},\\n  author={Decenci{\\\\`e}re, E and Cazuguel, G and Zhang, X and Thibault, G and Klein, J-C and Meyer, F and Marcotegui, B and Quellec, G and Lamard, M and Danno, R and others},\\n  journal={Innovation and Research in Biomedical Engineering},\\n  volume={34},\\n  number={2},\\n  pages={196--203},\\n  year={2013},\\n  publisher={Elsevier}\\n}\\n@article{rasti2018macular,\\n  title={Macular OCT classification using a multi-scale convolutional neural network ensemble},\\n  author={Rasti, R and Rabbani, H and Mehridehnavi, A and Hajizadeh, F},\\n  journal={IEEE Transactions on Medical Imaging},\\n  volume={37},\\n  number={4},\\n  pages={1024--1034},\\n  year={2018},\\n  publisher={IEEE}\\n}\\n@article{jahromi2014automatic,\\n  title={An automatic algorithm for segmentation of the boundaries of corneal layers in optical coherence tomography images using gaussian mixture model},\\n  author={Jahromi, MK and K, R and Rabbani, H and Dehnavi, AM and Peyman, A and Hajizadeh, F and Ommani, M},\\n  journal={Journal of Medical Signals and Sensors},\\n  volume={4},\\n  number={3},\\n  pages={171},\\n  year={2014},\\n  publisher={Wolters Kluwer--Medknow Publications}\\n}\\n@article{gholami2018octid,\\n  title={OCTID: Optical Coherence Tomography Image Database},\\n  author={Gholami, P and Roy, P and Parthasarathy, Ma K and Lakshminarayanan, V},\\n  journal={arXiv preprint arXiv:1812.07056},\\n  year={2018}\\n}\\n\\n@article{lowell2004optic,\\n  title={Optic nerve head segmentation},\\n  author={Lowell, J and Hunter, A and Steel, D and Basu, A and Ryder, R and Fletcher, E and Kennedy, L and others},\\n  journal={IEEE Transactions on Medical Imaging},\\n  volume={23},\\n  number={2},\\n  pages={256--264},\\n  year={2004}\\n}\\n@article{farsiu2014quantitative,\\n  title={Quantitative classification of eyes with and without intermediate age-related macular degeneration using optical coherence tomography},\\n  author={Farsiu, S and Chiu, SJ and O\\'Connell, RV and Folgar, FA and Yuan, Eric and Izatt, JA and Toth, CA and Age-Related Eye Disease Study 2 Ancillary Spectral Domain Optical Coherence Tomography Study Group and others},\\n  journal={Ophthalmology},\\n  volume={121},\\n  number={1},\\n  pages={162--172},\\n  year={2014},\\n  publisher={Elsevier}\\n}\\n@article{refuge,\\n  title= { Refuge. http://refuge.grand-challenge.org. 5th MICCAI Workshop on Ophthalmic Medical Image Analysis (OMIA)}\\n}\\n@article{mitry2013crowdsourcing,\\n  title={Crowdsourcing as a novel technique for retinal fundus photography classification: Analysis of Images in the EPIC Norfolk Cohort on behalf of the UKBiobank Eye and Vision Consortium},\\n  author={Mitry, D and Peto, T and Hayat, S and Morgan, JE and Khaw, K and Foster, PJ},\\n  journal={Plos One},\\n  volume={8},\\n  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America}\\n}\\n@article{mitra2018region,\\n  title={The region of interest localization for glaucoma analysis from retinal fundus image using deep learning},\\n  author={Mitra, A and Banerjee, PSh and Roy, S and Roy, S and Setua, SK},\\n  journal={Computer Methods and Programs in Biomedicine},\\n  volume={165},\\n  pages={25-35},\\n  year={2018},\\n  publisher={Elsevier}\\n}\\n@inproceedings{edupuganti2018automatic,\\n  title={Automatic Optic Disk and Cup Segmentation of Fundus Images Using Deep Learning},\\n  author={Edupuganti, VG and Chawla, A and Kale, A},\\n  booktitle={2018 25th IEEE International Conference on Image Processing (ICIP)},\\n  pages={2227--2231},\\n  year={2018}\\n}\\n@article{tan2017automated,\\n  title={Automated segmentation of exudates, haemorrhages, microaneurysms using single convolutional neural network},\\n  author={Tan, JH and Fujita, H and Sivaprasad, S and Bhandary, SV and Rao, AK and Chua, KC and Acharya, UR},\\n  journal={Information Sciences},\\n  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Ourselin S., Joskowicz L., Sabuncu M., Unal G., Wells W.},\\n  volume={9901},\\n  pages={140--148},\\n  year={2016},\\n  organization={Springer}\\n}\\n@inproceedings{lim2015integrated,\\n  title={Integrated optic disc and cup segmentation with deep learning},\\n  author={Lim, G and Cheng, Y and Hsu, W and Lee, ML},\\n  booktitle={Tools with Artificial Intelligence (ICTAI), 2015 IEEE 27th International Conference on},\\n  pages={162--169},\\n  year={2015}\\n}\\n@article{liu2018deep,\\n  title={A Deep Learning-Based Algorithm Identifies Glaucomatous Discs Using Monoscopic Fundus Photographs},\\n  author={Liu, S and Graham, SL and Schulz, A and Kalloniatis, M and Zangerl, B and Cai, W and Gao, Y and Chua, B and Arvind, H and Grigg, J and others},\\n  journal={Ophthalmology Glaucoma},\\n  volume={1},\\n  number={1},\\n  pages={15--22},\\n  year={2018},\\n  publisher={Elsevier}\\n}\\n@article{fang2017automatic,\\n  title={Automatic segmentation of nine retinal layer boundaries in OCT images of non-exudative AMD patients using deep learning and graph search},\\n  author={Fang, L and Cunefare, D and Wang, C and Guymer, RH and Li, S and Farsiu, S},\\n  journal={Biomedical Optics Express},\\n  volume={8},\\n  number={5},\\n  pages={2732--2744},\\n  year={2017},\\n  publisher={Optical Society of America}\\n}\\n@article{pekala2018deep,\\n  title={Deep Learning based Retinal OCT Segmentation},\\n  author={Pekala, M and Joshi, N and Freund, DE and Bressler, NM and DeBuc, DC and Burlina, PM},\\n  journal={arXiv preprint arXiv:1801.09749},\\n  year={2018}\\n}\\n@article{ben2017retinal,\\n  title={Retinal layers segmentation using Fully Convolutional Network in OCT images},\\n  author={Ben-Cohen, A and Mark, D and Kovler, I and Zur, D and Barak, A and Iglicki, M and Soferman, R},\\n  journal={RSIP Vision},\\n  year={2017}\\n}\\n@article{liu2018automated,\\n  title={Automated Layer Segmentation of Retinal Optical Coherence Tomography Images Using a Deep Feature Enhanced Structured Random Forests Classifier},\\n  author={Liu, X and Fu, T and Pan, Z and Liu, D and Hu, W and Liu, J and Zhang, K},\\n  journal={IEEE journal of Biomedical and Health Informatics},\\n  pages={1-1},\\n  year={2018},\\n  publisher={IEEE}\\n}\\n@article{welikala2016automated,\\n  title={Automated retinal image quality assessment on the UK Biobank dataset for epidemiological studies},\\n  author={Welikala, RA and Fraz, MM and Foster, PJ and Whincup, PH and Rudnicka, AR and Owen, CG and Strachan, DP and Barman, SA and others},\\n  journal={Computers in Biology and Medicine},\\n  volume={71},\\n  pages={67--76},\\n  year={2016},\\n  publisher={Elsevier}\\n}\\n@article{oliveira2018retinal,\\n  title={Retinal Vessel Segmentation based on Fully Convolutional Neural Networks},\\n  author={Oliveira, AFM and Pereira, SRM and Silva, CAB},\\n  journal={Expert Systems with Applications},\\n  volume={112},\\n  pages={229-242},\\n  year={2018},\\n  publisher={Elsevier}\\n}\\n@article{liu2018retinal,\\n  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pages={2369--2380},\\n  year={2016},\\n  publisher={IEEE}\\n}\\n@inproceedings{fu2016retinal,\\n  title={Retinal vessel segmentation via deep learning network and fully-connected conditional random fields},\\n  author={Fu, H and Xu, Y and Wong, DWK and Liu, J},\\n  booktitle={Biomedical Imaging (ISBI), 2016 IEEE 13th International Symposium on},\\n  pages={698--701},\\n  year={2016}\\n}\\n@article{orlando2018ensemble,\\n  title={An ensemble deep learning based approach for red lesion detection in fundus images},\\n  author={Orlando, JI and Prokofyeva, E and del Fresno, M and Blaschko, MB},\\n  journal={Computer Methods and Programs in Biomedicine},\\n  volume={153},\\n  pages={115--127},\\n  year={2018},\\n  publisher={Elsevier}\\n}\\n@article{van2016fast,\\n  title={Fast convolutional neural network training using selective data sampling: application to hemorrhage detection in color fundus images},\\n  author={van Grinsven, MJJP and van Ginneken, B and Hoyng, CB and Theelen, T and S{\\\\\\'a}nchez, CI},\\n  journal={IEEE Transactions on Medical Imaging},\\n  volume={35},\\n  number={5},\\n  pages={1273--1284},\\n  year={2016},\\n  publisher={IEEE}\\n}\\n@article{lam2018retinal,\\n  title={Retinal lesion detection with deep learning using image patches},\\n  author={Lam, C and Yu, C and Huang, L and Rubin, D},\\n  journal={Investigative Ophthalmology \\\\& Visual Science},\\n  volume={59},\\n  number={1},\\n  pages={590--596},\\n  year={2018},\\n  publisher={The Association for Research in Vision and Ophthalmology}\\n}\\n@article{abc,\\n  title={A deep learning algorithm for prediction of age-related eye disease study severity scale for age-related macular degeneration from color fundus photography},\\n  author={Grassmann, F., Mengelkamp, J., Brandl, C., Harsch, S., Zimmermann, M.E., Linkohr, B., Peters, A., Heid, I.M., Palm, C. and Weber, B.H.},\\n  journal={Ophthalmology},\\n  volume={125},\\n  pages={1410-1420},\\n  year={2018},\\n  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study in using universal deep features and transfer learning for automated AMD analysis},\\n  author={Burlina, P and Pacheco, KD and Joshi, N and Freund, DE and Bressler, NM},\\n  journal={Computers in Biology and Medicine},\\n  volume={82},\\n  pages={80--86},\\n  year={2017},\\n  publisher={Elsevier}\\n}\\n@inproceedings{govindaiah2018deep,\\n  title={Deep convolutional neural network based screening and assessment of age-related macular degeneration from fundus images},\\n  author={Govindaiah, A and Hussain, MdA and Smith, RT and Bhuiyan, A},\\n  booktitle={Biomedical Imaging (ISBI 2018), 2018 IEEE 15th International Symposium on},\\n  pages={1525--1528},\\n  year={2018},\\n  organization={IEEE}\\n}\\n@article{matsuba2018accuracy,\\n  author=\"Matsuba, S\\nand Tabuchi, H\\nand Ohsugi, H\\nand Enno, H\\nand Ishitobi, N\\nand Masumoto, H\\nand Kiuchi, Y\",\\ntitle=\"Accuracy of ultra-wide-field fundus ophthalmoscopy-assisted deep learning, a machine-learning technology, for detecting age-related macular degeneration\",\\njournal=\"International Ophthalmology\",\\nyear=\"2019\",\\nmonth=\"Jun\",\\nday=\"01\",\\nvolume=\"39\",\\nnumber=\"6\",\\npages=\"1269--1275\",\\nabstract=\"To predict exudative age-related macular degeneration (AMD), we combined a deep convolutional neural network (DCNN), a machine-learning algorithm, with Optos, an ultra-wide-field fundus imaging system.\",\\nissn=\"1573-2630\",\\ndoi=\"10.1007/s10792-018-0940-0\",\\nurl=\"https://doi.org/10.1007/s10792-018-0940-0\"\\n}\\n@article{tan2018age,\\n  title={Age-related Macular Degeneration detection using deep convolutional neural network},\\n  author={Tan, JH and Bhandary, SV and Sivaprasad, S and Hagiwara, Y and Bagchi, A and Raghavendra, U and Rao, AK and Raju, B and Shetty, NS and Gertych, A and others},\\n  journal={Future Generation Computer Systems},\\n  volume={87},\\n  pages={127--135},\\n  year={2018},\\n  publisher={Elsevier}\\n}\\n@article{treder2018automated,\\n  title={Automated detection of exudative age-related macular degeneration in spectral domain optical coherence tomography using deep learning},\\n  author={Treder, M and Lauermann, JL and Eter, N},\\n  journal={Graefe\\'s Archive for Clinical and Experimental Ophthalmology},\\n  volume={256},\\n  number={2},\\n  pages={259--265},\\n  year={2018},\\n  publisher={Springer}\\n}\\n@article{lee2016deep,\\n  title={Deep learning is effective for the classification of OCT images of normal versus Age-related Macular Degeneration},\\n  author={Lee, CS and Baughman, DM and Lee, AY},\\n  journal={arXiv preprint arXiv:1612.04891},\\n  year={2016}\\n}\\n@article{kermany2018identifying,\\n  title={Identifying medical diagnoses and treatable diseases by image-based deep learning},\\n  author={Kermany, DS and Goldbaum, M and Cai, W and Valentim, CCS and Liang, H and Baxter, SL and McKeown, A and Yang, G and Wu, X and Yan, F and others},\\n  journal={Cell},\\n  volume={172},\\n  number={5},\\n  pages={1122--1131},\\n  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Library}\\n}\\n@inproceedings{garcia2017detection,\\n  title={Detection of Diabetic Retinopathy Based on a Convolutional Neural Network Using Retinal Fundus Images},\\n  author={Garc{\\\\\\'\\\\i}a, G and Gallardo, J and Mauricio, A and L{\\\\\\'o}pez, J and Del Carpio, C},\\n  booktitle={International Conference on Artificial Neural Networks ed. 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Mori K., Sakuma I., Sato Y., Barillot C., Navab N.},\\n  volume={8150},\\n  pages={411--418},\\n  year={2013},\\n  organization={Springer}\\n}\\n@inproceedings{ciresan2012deep,\\n  title={Deep neural networks segment neuronal membranes in electron microscopy images},\\n  author={Ciresan, D and Giusti, A and Gambardella, LM and Schmidhuber, J},\\n  booktitle={Advances in Neural Information Processing Systems},\\n  pages={2843--2851},\\n  year={2012}\\n}\\n@article{sevastopolsky2017optic,\\n  title={Optic disc and cup segmentation methods for glaucoma detection with modification of U-Net convolutional neural network},\\n  author={Sevastopolsky, A},\\n  journal={Pattern Recognition and Image Analysis},\\n  volume={27},\\n  number={3},\\n  pages={618--624},\\n  year={2017},\\n  publisher={Springer}\\n}\\n@article{al2018multiscale,\\n  title={Multiscale sequential convolutional neural networks for simultaneous detection of fovea and optic disc},\\n  author={Al-Bander, B and Al-Nuaimy, W and Williams, B M and Zheng, Y},\\n  journal={Biomedical Signal Processing and Control},\\n  volume={40},\\n  pages={91-101},\\n  year={2018},\\n  publisher={Elsevier}\\n}\\n@article{xu2016stacked,\\n  title={Stacked sparse autoencoder (SSAE) for nuclei detection on breast cancer histopathology images},\\n  author={Xu, J and Xiang, L and Liu, Q and Gilmore, H and Wu, J and Tang, J and Madabhushi, A},\\n  journal={IEEE Transactions on Medical Imaging},\\n  volume={35},\\n  number={1},\\n  pages={119--130},\\n  year={2016},\\n  publisher={IEEE}\\n}\\n@article{annunziata2016accelerating,\\n  title={Accelerating convolutional sparse coding for curvilinear structures segmentation by refining SCIRD-TS filter banks},\\n  author={Annunziata, R and Trucco, E},\\n  journal={IEEE Transactions on Medical Imaging},\\n  volume={35},\\n  number={11},\\n  pages={2381--2392},\\n  year={2016},\\n  publisher={IEEE}\\n}\\n@inproceedings{melinvsvcak2015retinal,\\n  title={Retinal vessel segmentation using deep neural networks},\\n  author={Melin{\\\\v{s}}{\\\\v{c}}ak, M and Prenta{\\\\v{s}}i{\\\\\\'c}, P and Lon{\\\\v{c}}ari{\\\\\\'c}, S},\\n  booktitle={VISAPP 2015 (10th International Conference on Computer Vision Theory and Applications),vol 1},\\n  year={2015}\\n}\\n@article{cirecsan2012multi,\\n  title={Multi-column deep neural networks for image classification},\\n  author={Cire{\\\\c{s}}an, D and Meier, U and Schmidhuber, J},\\n  journal={arXiv preprint arXiv:1202.2745},\\n  year={2012}\\n}\\n@inproceedings{burlina2016detection,\\n  title={Detection of age-related macular degeneration via deep learning},\\n  author={Burlina, P and Freund, DE and Joshi, N and Wolfson, Y and Bressler, NM},\\n  booktitle={Biomedical Imaging (ISBI), 2016 IEEE 13th International Symposium on},\\n  pages={184--188},\\n  year={2016}\\n}\\n@inproceedings{noh2015learning,\\n  title={Learning deconvolution network for semantic segmentation},\\n  author={Noh, H and Hong, S and Han, B},\\n  booktitle={Proceedings of the IEEE International Conference on Computer Vision},\\n  pages={1520--1528},\\n  year={2015}\\n}\\n@inproceedings{chan2017transfer,\\n  title={Transfer learning for Diabetic Macular Edema (DME) detection on Optical Coherence Tomography (OCT) images},\\n  author={Chan, GCY and Muhammad, A and Shah, SAA and Tang, TB and Lu, C and Meriaudeau, F},\\n  booktitle={Signal and Image Processing Applications (ICSIPA), 2017 IEEE International Conference on},\\n  pages={493--496},\\n  year={2017}\\n}\\n@misc{lemaitre2016seri,\\n  title={Seri dataset},\\n  author={Lemaitre, G and Massich, J and Rastgoo, M and Meriaudeau, F},\\n  year={2016},\\n  publisher={Sep}\\n}\\n@article{fercher2003optical,\\n  title={Optical coherence tomography-principles and applications},\\n  author={Fercher, AF and Drexler, W and Hitzenberger, CK and Lasser, T},\\n  journal={Reports on Progress in Physics},\\n  volume={66},\\n  number={2},\\n  pages={239},\\n  year={2003},\\n  publisher={IOP Publishing}\\n}\\n@article{mo2018exudate,\\n  title={Exudate-based diabetic macular edema recognition in retinal images using cascaded deep residual networks},\\n  author={Mo, J and Zhang, L and Feng, Y},\\n  journal={Neurocomputing},\\n  volume={290},\\n  pages={161--171},\\n  year={2018},\\n  publisher={Elsevier}\\n}\\n@article{diaz2019retinal,\\n  title={Retinal Image Synthesis and Semi-supervised Learning for Glaucoma Assessment},\\n  author={Diaz-Pinto, A and Colomer, An and Naranjo, V and Morales, S and Xu, Y and Frangi, AF},\\n  journal={IEEE transactions on medical imaging},\\n  volume={38},\\n  pages={2211 - 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In: Stoyanov D. et al. (eds) Computational Pathology and Ophthalmic Medical Image Analysis. OMIA 2018, COMPAY 2018. Lecture Notes in Computer Science, vol 11039. pp 201-209 Springer, Cham},\\n  author={Lepetit-Aimon, G and Duval, R and Cheriet, F},\\n}\\n@inproceedings{chudzik2018discern,\\n  title={DISCERN: Generative Framework for Vessel Segmentation using Convolutional Neural Network and Visual Codebook},\\n  author={Chudzik, P and Al-Diri, B and Caliv{\\\\\\'a}, F and Hunter, A},\\n  booktitle={2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)},\\n  pages={5934--5937},\\n  year={2018}\\n}\\n@inproceedings{govindaiah2018new,\\n  title={A New and Improved Method for Automated Screening of Age-Related Macular Degeneration Using Ensemble Deep Neural Networks},\\n  author={Govindaiah, A and Smith, RT and Bhuiyan, A},\\n  booktitle={2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)},\\n  pages={702--705},\\n  year={2018}\\n}\\n@incollection{son2018classification,\\n  title={Classification of Findings with Localized Lesions in Fundoscopic Images Using a Regionally Guided CNN. 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depth imaging optical coherence tomography of the choroid in normal eyes},\\n  author={Margolis, Ron and Spaide, Richard F},\\n  journal={American journal of ophthalmology},\\n  volume={147},\\n  number={5},\\n  pages={811--815},\\n  year={2009},\\n  publisher={Elsevier}\\n}\\n@article{manjunath2010choroidal,\\n  title={Choroidal thickness in normal eyes measured using Cirrus HD optical coherence tomography},\\n  author={Manjunath, Varsha and Taha, Mohammad and Fujimoto, James G and Duker, Jay S},\\n  journal={American journal of ophthalmology},\\n  volume={150},\\n  number={3},\\n  pages={325--329},\\n  year={2010},\\n  publisher={Elsevier}\\n}\\n@article{manjunath2011analysis,\\n  title={Analysis of choroidal thickness in age-related macular degeneration using spectral-domain optical coherence tomography},\\n  author={Manjunath, Varsha and Goren, Jordana and Fujimoto, James G and Duker, Jay S},\\n  journal={American journal of ophthalmology},\\n  volume={152},\\n  number={4},\\n  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Association for Research in Vision and Ophthalmology}\\n}@article{regatieri2012choroidal,\\n  title={Choroidal thickness in patients with diabetic retinopathy analyzed by spectral-domain optical coherence tomography},\\n  author={Regatieri, Caio V and Branchini, Lauren and Carmody, Jill and Fujimoto, James G and Duker, Jay S},\\n  journal={Retina (Philadelphia, Pa.)},\\n  volume={32},\\n  number={3},\\n  pages={563},\\n  year={2012},\\n  publisher={NIH Public Access}\\n}\\n@article{imamura2009enhanced,\\n  title={Enhanced depth imaging optical coherence tomography of the choroid in central serous chorioretinopathy},\\n  author={Imamura, Yutaka and Fujiwara, Takamitsu and Margolis, RON and Spaide, Richard F},\\n  journal={Retina},\\n  volume={29},\\n  number={10},\\n  pages={1469--1473},\\n  year={2009},\\n  publisher={LWW}\\n}\\n@article{kim2011comparison,\\n  title={Comparison of choroidal thickness among patients with healthy eyes, early age-related maculopathy, neovascular 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Finger, Paul T},\\n  journal={British Journal of Ophthalmology},\\n  volume={96},\\n  number={2},\\n  pages={224--228},\\n  year={2012},\\n  publisher={BMJ Publishing Group Ltd}\\n}\\n@article{torres2011optical,\\n  title={Optical coherence tomography enhanced depth imaging of choroidal tumors},\\n  author={Torres, Virginia LL and Brugnoni, Nicole and Kaiser, Peter K and Singh, Arun D},\\n  journal={American journal of ophthalmology},\\n  volume={151},\\n  number={4},\\n  pages={586--593},\\n  year={2011},\\n  publisher={Elsevier}\\n}\\n@article{dhoot2013evaluation,\\n  title={Evaluation of choroidal thickness in retinitis pigmentosa using enhanced depth imaging optical coherence tomography},\\n  author={Dhoot, Dilsher S and Huo, Siya and Yuan, Alex and Xu, David and Srivistava, Sunil and Ehlers, Justis P and Traboulsi, Elias and Kaiser, Peter K},\\n  journal={British Journal of Ophthalmology},\\n  volume={97},\\n  number={1},\\n  pages={66--69},\\n  year={2013},\\n  publisher={BMJ Publishing Group Ltd}\\n}\\n@article{yeoh2010choroidal,\\n  title={Choroidal imaging in inherited retinal disease using the technique of enhanced depth imaging optical coherence tomography},\\n  author={Yeoh, Jonathan and Rahman, Waheeda and Chen, Fred and Hooper, Claire and Patel, Praveen and Tufail, Adnan and Webster, Andrew R and Moore, Anthony T and DaCruz, Lyndon},\\n  journal={Graefe\\'s Archive for Clinical and Experimental Ophthalmology},\\n  volume={248},\\n  number={12},\\n  pages={1719--1728},\\n  year={2010},\\n  publisher={Springer}\\n}\\n@article{witkin2006ultra,\\n  title={Ultra-high resolution optical coherence tomography assessment of photoreceptors in retinitis pigmentosa and related diseases},\\n  author={Witkin, Andre J and Ko, Tony H and Fujimoto, James G and Chan, Annie and Drexler, Wolfgang and Schuman, Joel S and Reichel, Elias and Duker, Jay S},\\n  journal={American journal of ophthalmology},\\n  volume={142},\\n  number={6},\\n  pages={945--952},\\n  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Shahab and Mayer, Markus A and Boretsky, Adam and Van Kuijk, Frederik J and Motamedi, Massoud},\\n  journal={Journal of biomedical optics},\\n  volume={17},\\n  number={11},\\n  pages={116009},\\n  year={2012},\\n  publisher={International Society for Optics and Photonics}\\n}\\n@inproceedings{yazdanpanah2009intra,\\n  title={Intra-retinal layer segmentation in optical coherence tomography using an active contour approach},\\n  author={Yazdanpanah, Azadeh and Hamarneh, Ghassan and Smith, Benjamin and Sarunic, Marinko},\\n  booktitle={International Conference on Medical Image Computing and Computer-Assisted Intervention},\\n  pages={649--656},\\n  year={2009},\\n  organization={Springer}\\n}\\n@article{savastano2014differential,\\n  title={Differential vulnerability of retinal layers to early age-related macular degeneration: evidence by SD-OCT segmentation analysis},\\n  author={Savastano, Maria Cristina and Minnella, Angelo Maria and Tamburrino, Antonello and Giovinco, Gaspare and Ventre, Salvatore and Falsini, Benedetto},\\n  journal={Investigative ophthalmology \\\\& visual science},\\n  volume={55},\\n  number={1},\\n  pages={560--566},\\n  year={2014},\\n  publisher={The Association for Research in Vision and Ophthalmology}\\n}\\n@article{kajic2012automated,\\n  title={Automated choroidal segmentation of 1060 nm OCT in healthy and pathologic eyes using a statistical model},\\n  author={Kaji{\\\\\\'c}, Vedran and Esmaeelpour, Marieh and Pova{\\\\v{z}}ay, Boris and Marshall, David and Rosin, Paul L and Drexler, Wolfgang},\\n  journal={Biomedical optics express},\\n  volume={3},\\n  number={1},\\n  pages={86--103},\\n  year={2012},\\n  publisher={Optical Society of America}\\n}\\n@article{vermeer2011automated,\\n  title={Automated segmentation by pixel classification of retinal layers in ophthalmic OCT images},\\n  author={Vermeer, KA and Van der Schoot, J and Lemij, HG and De Boer, JF},\\n  journal={Biomedical optics express},\\n  volume={2},\\n  number={6},\\n  pages={1743--1756},\\n  year={2011},\\n  publisher={Optical Society of America}\\n}\\n@article{lang2013retinal,\\n  title={Retinal layer segmentation of macular OCT images using boundary classification},\\n  author={Lang, Andrew and Carass, Aaron and Hauser, Matthew and Sotirchos, Elias S and Calabresi, Peter A and Ying, Howard S and Prince, Jerry L},\\n  journal={Biomedical optics express},\\n  volume={4},\\n  number={7},\\n  pages={1133--1152},\\n  year={2013},\\n  publisher={Optical Society of America}\\n}\\n@article{chen2013automated,\\n  title={Automated drusen segmentation and quantification in SD-OCT images},\\n  author={Chen, Qiang and Leng, Theodore and Zheng, Luoluo and Kutzscher, Lauren and Ma, Jeffrey and de Sisternes, Luis and Rubin, Daniel L},\\n  journal={Medical image analysis},\\n  volume={17},\\n  number={8},\\n  pages={1058--1072},\\n  year={2013},\\n  publisher={Elsevier}\\n}\\n@article{bizios2010machine,\\n  title={Machine learning classifiers for glaucoma diagnosis based on classification of retinal nerve fibre layer thickness parameters measured by Stratus OCT},\\n  author={Bizios, Dimitrios and Heijl, Anders and Hougaard, Jesper Leth and Bengtsson, Boel},\\n  journal={Acta ophthalmologica},\\n  volume={88},\\n  number={1},\\n  pages={44--52},\\n  year={2010},\\n  publisher={Wiley Online Library}\\n}\\n@inproceedings{anantrasirichai2013svm,\\n  title={S\\\\uppercase{VM}-based texture classification in optical coherence tomography},\\n  author={Anantrasirichai, Nantheera and Achim, Alin and Morgan, James E and Erchova, Irina and Nicholson, Lindsay},\\n  booktitle={2013 IEEE 10th International Symposium on Biomedical Imaging},\\n  pages={1332--1335},\\n  year={2013},\\n  organization={IEEE}\\n}\\n@article{alsaih2017machine,\\n  title={Machine learning techniques for diabetic macular edema (DME) classification on SD-OCT images},\\n  author={Alsaih, Khaled and Lemaitre, Guillaume and Rastgoo, Mojdeh and Massich, Joan and Sidib{\\\\\\'e}, D{\\\\\\'e}sir{\\\\\\'e} and Meriaudeau, Fabrice},\\n  journal={Biomedical engineering online},\\n  volume={16},\\n  number={1},\\n  pages={68},\\n  year={2017},\\n  publisher={BioMed Central}\\n}\\n@inproceedings{goodfellow2014generative,\\n  title={Generative adversarial nets},\\n  author={Goodfellow, Ian and Pouget-Abadie, Jean and Mirza, Mehdi and Xu, Bing and Warde-Farley, David and Ozair, Sherjil and Courville, Aaron and Bengio, Yoshua},\\n  booktitle={Advances in neural information processing systems},\\n  pages={2672--2680},\\n  year={2014}\\n}\\n@article{mirza2014conditional,\\n  title={Conditional generative adversarial nets},\\n  author={Mirza, Mehdi and Osindero, Simon},\\n  journal={arXiv preprint arXiv:1411.1784},\\n  year={2014}\\n}\\n@article{ma2018speckle,\\n  title={Speckle noise reduction in optical coherence tomography images based on edge-sensitive cGAN},\\n  author={Ma, Yuhui and Chen, Xinjian and Zhu, Weifang and Cheng, Xuena and Xiang, Dehui and Shi, Fei},\\n  journal={Biomedical optics express},\\n  volume={9},\\n  number={11},\\n  pages={5129--5146},\\n  year={2018},\\n  publisher={Optical Society of America}\\n}\\n@inproceedings{zha2019generation,\\n  title={Generation of retinal OCT images with diseases based on cGAN},\\n  author={Zha, Xuewei and Shi, Fei and Ma, Yuhui and Zhu, Weifang and Chen, Xinjian},\\n  booktitle={Medical Imaging 2019: Image Processing},\\n  volume={10949},\\n  pages={1094924},\\n  year={2019},\\n  organization={International Society for Optics and Photonics}\\n}\\n@article{huang2019simultaneous,\\n  title={Simultaneous denoising and super-resolution of optical coherence tomography images based on generative adversarial network},\\n  author={Huang, Yongqiang and Lu, Zexin and Shao, Zhimin and Ran, Maosong and Zhou, Jiliu and Fang, Leyuan and Zhang, Yi},\\n  journal={Optics express},\\n  volume={27},\\n  number={9},\\n  pages={12289--12307},\\n  year={2019},\\n  publisher={Optical Society of America}\\n}\\n@article{dos2019corneanet,\\n  title={CorneaNet: fast segmentation of cornea OCT scans of healthy and keratoconic eyes using deep learning},\\n  author={Dos Santos, Valentin Aranha and Schmetterer, Leopold and Stegmann, Hannes and Pfister, Martin and Messner, Alina and Schmidinger, Gerald and Garhofer, Gerhard and Werkmeister, Ren{\\\\\\'e} M},\\n  journal={Biomedical optics express},\\n  volume={10},\\n  number={2},\\n  pages={622--641},\\n  year={2019},\\n  publisher={Optical Society of America}\\n}\\n@article{liu2019robust,\\n  title={Robust deep learning method for choroidal vessel segmentation on swept source optical coherence tomography images},\\n  author={Liu, Xiaoxiao and Bi, Lei and Xu, Yupeng and Feng, Dagan and Kim, Jinman and Xu, Xun},\\n  journal={Biomedical optics express},\\n  volume={10},\\n  number={4},\\n  pages={1601--1612},\\n  year={2019},\\n  publisher={Optical Society of America}\\n}\\n@article{kugelman2019automatic,\\n  title={Automatic choroidal segmentation in OCT images using supervised deep learning methods},\\n  author={Kugelman, Jason and Alonso-Caneiro, David and Read, Scott A and Hamwood, Jared and Vincent, Stephen J and Chen, Fred K and Collins, Michael J},\\n  journal={Scientific reports},\\n  volume={9},\\n  number={1},\\n  pages={1--13},\\n  year={2019},\\n  publisher={Nature Publishing Group}\\n}\\n@inproceedings{tennakoon2018retinal,\\n  title={Retinal fluid segmentation in OCT images using adversarial loss based convolutional neural networks},\\n  author={Tennakoon, Ruwan and Gostar, Amirali K and Hoseinnezhad, Reza and Bab-Hadiashar, Alireza},\\n  booktitle={2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018)},\\n  pages={1436--1440},\\n  year={2018},\\n  organization={IEEE}\\n}\\n@article{asgari2019multiclass,\\n  title={Multiclass segmentation as multitask learning for drusen segmentation in retinal optical coherence tomography},\\n  author={Asgari, Rhona and Orlando, Jos{\\\\\\'e} Ignacio 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Parasympathomimetic, sympathomimetic and sympatholytics},\\n  author={Costagliola, Ciro and Dell\\'Omo, Roberto and Romano, Mario R and Rinaldi, Michele and Zeppa, Lucia and Parmeggiani, Francesco},\\n  journal={Expert opinion on Pharmacotherapy},\\n  volume={10},\\n  number={16},\\n  pages={2663--2677},\\n  year={2009},\\n  publisher={Taylor \\\\& Francis}\\n}\\n@article{krolewski1986risk,\\n  title={Risk of proliferative diabetic retinopathy in juvenile-onset type I diabetes: a 40-yr follow-up study},\\n  author={Krolewski, AS and Warram, JH and Rand, LI and Christlieb, AR and Busick, EJ and Kahn, CR},\\n  journal={Diabetes care},\\n  volume={9},\\n  number={5},\\n  pages={443--452},\\n  year={1986},\\n  publisher={Am Diabetes Assoc}\\n}\\n@article{strimbu2010biomarkers,\\n  title={What are biomarkers?},\\n  author={Strimbu, Kyle and Tavel, Jorge A},\\n  journal={Current Opinion in HIV and AIDS},\\n  volume={5},\\n  number={6},\\n  pages={463},\\n  year={2010},\\n  publisher={NIH Public Access}\\n}\\n@book{kanski2009clinical,\\n  title={Clinical ophthalmology: a synopsis},\\n  author={Kanski, Jack J},\\n  year={2009},\\n  publisher={Elsevier Health Sciences}\\n}\\n@article{zachariah2015grading,\\n  title={Grading diabetic retinopathy (DR) using the Scottish grading protocol},\\n  author={Zachariah, Sonia and Wykes, William and Yorston, David},\\n  journal={Community eye health},\\n  volume={28},\\n  number={92},\\n  pages={72},\\n  year={2015},\\n  publisher={International Centre for Eye Health}\\n}\\n@article{fornell2011advantages,\\n  title={The Advantages and Disadvantages of OCT vs. IVUS},\\n  author={Fornell, Dave},\\n  journal={Diagnostic and Interventional Cardiology},\\n  pages={1--4},\\n  year={2011}\\n}\\n@article{leitgeb2003performance,\\n  title={Performance of fourier domain vs. time domain optical coherence tomography},\\n  author={Leitgeb, R and Hitzenberger, CK and Fercher, Adolf F},\\n  journal={Optics express},\\n  volume={11},\\n  number={8},\\n  pages={889--894},\\n  year={2003},\\n  publisher={Optical Society of America}\\n}\\n@article{bezerra2009intracoronary,\\n  title={Intracoronary optical coherence tomography: a comprehensive review: clinical and research applications},\\n  author={Bezerra, Hiram G and Costa, Marco A and Guagliumi, Giulio and Rollins, Andrew M and Simon, Daniel I},\\n  journal={JACC: Cardiovascular Interventions},\\n  volume={2},\\n  number={11},\\n  pages={1035--1046},\\n  year={2009},\\n  publisher={JACC: Cardiovascular Interventions}\\n}\\n@article{de2017polarization,\\n  title={Polarization sensitive optical coherence tomography--a review},\\n  author={De Boer, Johannes F and Hitzenberger, Christoph K and Yasuno, Yoshiaki},\\n  journal={Biomedical optics express},\\n  volume={8},\\n  number={3},\\n  pages={1838--1873},\\n  year={2017},\\n  publisher={Optical Society of America}\\n}\\n@article{baumann2017polarization,\\n  title={Polarization sensitive optical coherence tomography: a review of technology and applications},\\n  author={Baumann, Bernhard},\\n  journal={Applied Sciences},\\n  volume={7},\\n  number={5},\\n  pages={474},\\n  year={2017},\\n  publisher={Multidisciplinary Digital Publishing Institute}\\n}\\n@article{kishi2016impact,\\n  title={Impact of swept source optical coherence tomography on ophthalmology},\\n  author={Kishi, Shoji},\\n  journal={Taiwan journal of ophthalmology},\\n  volume={6},\\n  number={2},\\n  pages={58--68},\\n  year={2016},\\n  publisher={Elsevier}\\n}\\n@article{trick2008mri,\\n  title={MRI retinovascular studies in humans: research in patients with diabetes},\\n  author={Trick, Gary L and Edwards, Paul A and Desai, Uday and Morton, Paula E and Latif, Zahid and Berkowitz, Bruce A},\\n  journal={NMR in Biomedicine: An International Journal Devoted to the Development and Application of Magnetic Resonance In vivo},\\n  volume={21},\\n  number={9},\\n  pages={1003--1012},\\n  year={2008},\\n  publisher={Wiley Online Library}\\n}\\n@article{townsend2008clinical,\\n  title={Clinical application of MRI in ophthalmology},\\n  author={Townsend, Kelly A and Wollstein, Gadi and Schuman, Joel S},\\n  journal={NMR in Biomedicine: An International Journal Devoted to the Development and Application of Magnetic Resonance In vivo},\\n  volume={21},\\n  number={9},\\n  pages={997--1002},\\n  year={2008},\\n  publisher={Wiley Online Library}\\n}\\n@article{poplin2018prediction,\\n  title={Prediction of cardiovascular risk factors from retinal fundus photographs via deep learning},\\n  author={Poplin, Ryan and Varadarajan, Avinash V and Blumer, Katy and Liu, Yun and McConnell, Michael V and Corrado, Greg S and Peng, Lily and Webster, Dale R},\\n  journal={Nature Biomedical Engineering},\\n  volume={2},\\n  number={3},\\n  pages={158},\\n  year={2018},\\n  publisher={Nature Publishing Group}\\n}\\n@article{garway1998vertical,\\n  title={Vertical cup/disc ratio in relation to optic disc size: its value in the assessment of the glaucoma suspect},\\n  author={Garway-Heath, David F and Ruben, Simon T and Viswanathan, Ananth and Hitchings, Roger A},\\n  journal={British Journal of Ophthalmology},\\n  volume={82},\\n  number={10},\\n  pages={1118--1124},\\n  year={1998},\\n  publisher={BMJ Publishing Group Ltd}\\n}\\n@article{jaffe2004optical,\\n  title={Optical coherence tomography to detect and manage retinal disease and glaucoma},\\n  author={Jaffe, Glenn J and Caprioli, Joseph},\\n  journal={American journal of ophthalmology},\\n  volume={137},\\n  number={1},\\n  pages={156--169},\\n  year={2004},\\n  publisher={Elsevier}\\n}\\n@article{klein1994hypertension,\\n  title={Hypertension and retinopathy, arteriolar narrowing, and arteriovenous nicking in a population},\\n  author={Klein, Ronald and Klein, Barbara EK and Moss, Scot E and Wang, Qin},\\n  journal={Archives of ophthalmology},\\n  volume={112},\\n  number={1},\\n  pages={92--98},\\n  year={1994},\\n  publisher={American Medical Association}\\n}\\n@article{cheung2011retinal,\\n  title={Retinal vascular tortuosity, blood pressure, and cardiovascular risk factors},\\n  author={Cheung, Carol Yim-lui and Zheng, Yingfeng and Hsu, Wynne and Lee, Mong Li and Lau, Qiangfeng Peter and Mitchell, Paul and Wang, Jie Jin and Klein, Ronald and Wong, Tien Yin},\\n  journal={Ophthalmology},\\n  volume={118},\\n  number={5},\\n  pages={812--818},\\n  year={2011},\\n  publisher={Elsevier}\\n}\\n@article{liao2018potential,\\n  title={Potential utility of retinal imaging for Alzheimer’s Disease: a review},\\n  author={Liao, Huan and Zhu, Zhuoting and Peng, Ying},\\n  journal={Frontiers in aging neuroscience},\\n  volume={10},\\n  year={2018},\\n  publisher={Frontiers Media SA}\\n}\\n@article{von2018retinal,\\n  title={Retinal volume change is a reliable OCT biomarker for disease activity in neovascular AMD},\\n  author={von der Burchard, Claus and Treumer, Felix and Ehlken, Christoph and Koinzer, Stefan and Purtskhvanidze, Konstantine and Tode, Jan and Roider, Johann},\\n  journal={Graefe\\'s Archive for Clinical and Experimental Ophthalmology},\\n  volume={256},\\n  number={9},\\n  pages={1623--1629},\\n  year={2018},\\n  publisher={Springer}\\n}\\n@article{vidal2018intraretinal,\\n  title={Intraretinal fluid identification via enhanced maps using optical coherence tomography images},\\n  author={Vidal, Pl{\\\\\\'a}cido L and de Moura, Joaquim and Novo, Jorge and Penedo, Manuel G and Ortega, Marcos},\\n  journal={Biomedical optics express},\\n  volume={9},\\n  number={10},\\n  pages={4730--4754},\\n  year={2018},\\n  publisher={Optical Society of America}\\n}\\n@article{durbin2017quantification,\\n  title={Quantification of retinal microvascular density in optical coherence tomographic angiography images in diabetic retinopathy},\\n  author={Durbin, Mary K and An, Lin and Shemonski, Nathan D and Soares, M{\\\\\\'a}rio and Santos, Torcato and Lopes, Marta and Neves, Catarina and Cunha-Vaz, Jose},\\n  journal={JAMA ophthalmology},\\n  volume={135},\\n  number={4},\\n  pages={370--376},\\n  year={2017},\\n  publisher={American Medical Association}\\n}\\n@article{jenkins2015biomarkers,\\n  title={Biomarkers in diabetic retinopathy},\\n  author={Jenkins, Alicia J and Joglekar, Mugdha V and Hardikar, Anandwardhan A and Keech, Anthony C and O\\'Neal, David N and Januszewski, Andrzej S},\\n  journal={The review of diabetic studies: RDS},\\n  volume={12},\\n  number={1-2},\\n  pages={159},\\n  year={2015},\\n  publisher={Society for Biomedical Diabetes Research}\\n}\\n@article{sonoda2013correlation,\\n  title={Correlation between reflectivity of subretinal fluid in OCT images and concentration of intravitreal VEGF in eyes with diabetic macular edema},\\n  author={Sonoda, Shozo and Sakamoto, Taiji and Shirasawa, Makoto and Yamashita, Takehiro and Otsuka, Hiroki and Terasaki, Hiroto},\\n  journal={Investigative ophthalmology \\\\& visual science},\\n  volume={54},\\n  number={8},\\n  pages={5367--5374},\\n  year={2013},\\n  publisher={The Association for Research in Vision and Ophthalmology}\\n}\\n@article{wang2017automated,\\n  title={Automated detection of photoreceptor disruption in mild diabetic retinopathy on volumetric optical coherence tomography},\\n  author={Wang, Zhuo and Camino, Acner and Zhang, Miao and Wang, Jie and Hwang, Thomas S and Wilson, David J and Huang, David and Li, Dengwang and Jia, Yali},\\n  journal={Biomedical optics express},\\n  volume={8},\\n  number={12},\\n  pages={5384--5398},\\n  year={2017},\\n  publisher={Optical Society of America}\\n}\\n@article{reiter2019impact,\\n  title={Impact of Drusen Volume on Quantitative Fundus Autofluorescence in Early and Intermediate Age-Related Macular Degeneration},\\n  author={Reiter, Gregor Sebastian and Told, Reinhard and Schlanitz, Ferdinand Georg and Bogunovic, Hrvoje and Baumann, Lukas and Sacu, Stefan and Schmidt-Erfurth, Ursula and Pollreisz, Andreas},\\n  journal={Investigative ophthalmology \\\\& visual science},\\n  volume={60},\\n  number={6},\\n  pages={1937--1942},\\n  year={2019},\\n  publisher={The Association for Research in Vision and Ophthalmology}\\n}\\n@article{phadikar2017potential,\\n  title={The potential of spectral domain optical coherence tomography imaging based retinal biomarkers},\\n  author={Phadikar, Prateep and Saxena, Sandeep and Ruia, Surabhi and Lai, Timothy YY and Meyer, Carsten H and Eliott, Dean},\\n  journal={International journal of retina and vitreous},\\n  volume={3},\\n  number={1},\\n  pages={1},\\n  year={2017},\\n  publisher={BioMed Central}\\n}\\n@article{pichi2018choroidal,\\n  title={Choroidal biomarkers},\\n  author={Pichi, Francesco and Aggarwal, Kanika and Neri, Piergiorgio and Salvetti, Paola and Lembo, Andrea and Nucci, Paolo and Cheung, Chui Ming Gemmy and Gupta, Vishali},\\n  journal={Indian journal of ophthalmology},\\n  volume={66},\\n  number={12},\\n  pages={1716},\\n  year={2018},\\n  publisher={Wolters Kluwer--Medknow Publications}\\n}\\n@article{schmidt2018prediction,\\n  title={Prediction of individual disease conversion in early AMD using artificial intelligence},\\n  author={Schmidt-Erfurth, Ursula and Waldstein, Sebastian M and Klimscha, Sophie and Sadeghipour, Amir and Hu, Xiaofeng and Gerendas, Bianca S and Osborne, Aaron and Bogunovi{\\\\\\'c}, Hrvoje},\\n  journal={Investigative ophthalmology \\\\& visual science},\\n  volume={59},\\n  number={8},\\n  pages={3199--3208},\\n  year={2018},\\n  publisher={The Association for Research in Vision and Ophthalmology}\\n}\\n@article{or2018imaging,\\n  title={How Imaging Can Identify Predictive Biomarkers of AMD},\\n  author={Or, Chris and Liu, Keke and Waheed, Nadia},\\n  year={2018}\\n}\\n@article{curcio2017activated,\\n  title={Activated retinal pigment epithelium, an optical coherence tomography biomarker for progression in age-related macular degeneration},\\n  author={Curcio, Christine A and Zanzottera, Emma C and Ach, Thomas and Balaratnasingam, Chandrakumar and Freund, K Bailey},\\n  journal={Investigative ophthalmology \\\\& visual science},\\n  volume={58},\\n  number={6},\\n  pages={BIO211--BIO226},\\n  year={2017},\\n  publisher={The Association for Research in Vision and Ophthalmology}\\n}\\n@article{rabiolo2017spotlight,\\n  title={Spotlight on reticular pseudodrusen},\\n  author={Rabiolo, Alessandro and Sacconi, Riccardo and Cicinelli, Maria Vittoria and Querques, Lea and Bandello, Francesco and Querques, Giuseppe},\\n  journal={Clinical ophthalmology (Auckland, NZ)},\\n  volume={11},\\n  pages={1707},\\n  year={2017},\\n  publisher={Dove Press}\\n}\\n@article{kermany2018labeled,\\n  title={Labeled optical coherence tomography (OCT) and Chest X-Ray images for classification},\\n  author={Kermany, DK and Goldbaum, M},\\n  journal={Mendeley Data},\\n  volume={2},\\n  year={2018}\\n}\\n@article{bogunovic2019retouch,\\n  title={RETOUCH-The Retinal OCT Fluid Detection and Segmentation Benchmark and Challenge},\\n  author={Bogunovi{\\\\\\'c}, Hrvoje and Venhuizen, Freerk and Klimscha, Sophie and Apostolopoulos, Stefanos and Bab-Hadiashar, Alireza and Bagci, Ulas and Beg, Mirza Faisal and Bekalo, Loza and Chen, Qiang and Ciller, Carlos and others},\\n  journal={IEEE transactions on medical imaging},\\n  year={2019},\\n  publisher={IEEE}\\n}\\n@misc{eye_anatomy,\\n  title = {Eye Anatomy},\\n  howpublished = {\\\\url{https://www.drwylie.com/eye-health/eye-anatomy}},\\n  note = {Accessed: 2019-10-29}\\n}\\n@inproceedings{kurmann2019fused,\\n  title={Fused Detection of Retinal Biomarkers in OCT Volumes},\\n  author={Kurmann, Thomas and M{\\\\\\'a}rquez-Neila, Pablo and Yu, Siqing and Munk, Marion and Wolf, Sebastian and Sznitman, Raphael},\\n  booktitle={International Conference on Medical Image Computing and Computer-Assisted Intervention},\\n  pages={255--263},\\n  year={2019},\\n  organization={Springer}\\n}\\n@article{bhende2018optical,\\n  title={Optical coherence tomography: A guide to interpretation of common macular diseases},\\n  author={Bhende, Muna and Shetty, Sharan and Parthasarathy, Mohana Kuppuswamy and Ramya, S},\\n  journal={Indian journal of ophthalmology},\\n  volume={66},\\n  number={1},\\n  pages={20},\\n  year={2018},\\n  publisher={Wolters Kluwer--Medknow Publications}\\n}\\n@misc{ps_oct,\\n  title = {Polarization sensitive OCT},\\n  howpublished = {\\\\url{https://zmpbmt.meduniwien.ac.at/wissenschaft-forschung/optical-imaging/functional-and-contrast-enhanced-imaging/polarization-sensitive-oct/}},\\n  note = {Accessed: 2019-10-29}\\n}\\n@incollection{sherman1989history,\\n  title={The history of the ophthalmoscope},\\n  author={Sherman, Spencer E},\\n  booktitle={History of Ophthalmology},\\n  pages={221--228},\\n  year={1989},\\n  publisher={Springer}\\n}\\n@article{venguibn,\\n  title={Ibn al-Haytham: Founder of Physiological Optics?},\\n  author={In:  R.Rashed, A.Boudrioua, V. Lakshminarayanan},\\n  journal={Light Based Science: Technology and Sustainable Development},\\n  chapter={6},\\n  number={1},\\n  pages={63-108},\\n  year={2017},\\n  publisher={CRC Press,Boca raton, FL}\\n}\\n@article{kim2014convolutional,\\n  title={Convolutional neural networks for sentence classification},\\n  author={Kim, Yoon},\\n  journal={arXiv preprint arXiv:1408.5882},\\n  year={2014}\\n}\\n@inproceedings{nair2010rectified,\\n  title={Rectified linear units improve restricted boltzmann machines},\\n  author={Nair, Vinod and Hinton, Geoffrey E},\\n  booktitle={Proceedings of the 27th international conference on machine learning (ICML-10)},\\n  pages={807--814},\\n  year={2010}\\n}\\n@incollection{hecht1992theory,\\n  title={Theory of the backpropagation neural network},\\n  author={Hecht-Nielsen, Robert},\\n  booktitle={Neural networks for perception},\\n  pages={65--93},\\n  year={1992},\\n  publisher={Elsevier}\\n}\\n@inproceedings{scherer2010evaluation,\\n  title={Evaluation of pooling operations in convolutional architectures for object recognition},\\n  author={Scherer, Dominik and M{\\\\\"u}ller, Andreas and Behnke, Sven},\\n  booktitle={International conference on artificial neural networks},\\n  pages={92--101},\\n  year={2010},\\n  organization={Springer}\\n}\\n@inproceedings{szegedy2016rethinking,\\n  title={Rethinking the inception architecture for computer vision},\\n  author={Szegedy, Christian and Vanhoucke, Vincent and Ioffe, Sergey and Shlens, Jon and Wojna, Zbigniew},\\n  booktitle={Proceedings of the IEEE conference on computer vision and pattern recognition},\\n  pages={2818--2826},\\n  year={2016}\\n}\\n@inproceedings{sengupta2019cross,\\n  title={Cross-domain diabetic retinopathy detection using deep learning},\\n  author={Sengupta, Sourya and Singh, Amitojdeep and Zelek, John and Lakshminarayanan, Vasudevan},\\n  booktitle={Applications of Machine Learning},\\n  volume={11139},\\n  pages={111390V},\\n  year={2019},\\n  organization={International Society for Optics and Photonics}\\n}\\n@inproceedings{singh2019glaucoma,\\n  title={Glaucoma diagnosis using transfer learning methods},\\n  author={Singh, Amitojdeep and Sengupta, Sourya and Lakshminarayanan, Vasudevan},\\n  booktitle={Applications of Machine Learning},\\n  volume={11139},\\n  pages={111390U},\\n  year={2019},\\n  organization={International Society for Optics and Photonics}\\n}\\n@inproceedings{gholami2018intra,\\n  title={Intra-retinal segmentation of optical coherence tomography images using active contours with a dynamic programming initialization and an adaptive weighting strategy},\\n  author={Gholami, Peyman and Roy, Priyanka and Parthasarathy, Mohana Kuppuswamy and Ommani, Abbas and Zelek, John and Lakshminarayanan, Vasudevan},\\n  booktitle={Optical Coherence Tomography and Coherence Domain Optical Methods in Biomedicine XXII},\\n  volume={10483},\\n  pages={104832M},\\n  year={2018},\\n  organization={International Society for Optics and Photonics}\\n}`\\n@article{cortes1995support,\\n  title={Support-vector networks},\\n  author={Cortes, Corinna and Vapnik, Vladimir},\\n  journal={Machine learning},\\n  volume={20},\\n  number={3},\\n  pages={273--297},\\n  year={1995},\\n  publisher={Springer}\\n}\\n@article{liaw2002classification,\\n  title={Classification and regression by randomForest},\\n  author={Liaw, Andy and Wiener, Matthew and others},\\n  journal={R news},\\n  volume={2},\\n  number={3},\\n  pages={18--22},\\n  year={2002}\\n}\\n@article{sarle1994neural,\\n  title={Neural networks and statistical models},\\n  author={Sarle, Warren S},\\n  year={1994},\\n  publisher={Citeseer}\\n}\\n@article{fujimoto2016development,\\n  title={The development, commercialization, and impact of optical coherence tomography},\\n  author={Fujimoto, James and Swanson, Eric},\\n  journal={Investigative ophthalmology \\\\& visual science},\\n  volume={57},\\n  number={9},\\n  pages={OCT1--OCT13},\\n  year={2016},\\n  publisher={The Association for Research in Vision and Ophthalmology}\\n}'"
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     "text": [
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      "Found and included in lastname :  and S{\\'a}\n",
      "Found and included in lastname : d Alay{\\'o}\n",
      "Found and included in lastname : d Rinc{\\'o}\n",
      "Found and included in lastname :  Arbel{\\'a}\n",
      "Found and included in lastname :  and S{\\'a}\n",
      "Found and included in lastname :  and L{\\'o}\n",
      "Found and included in lastname :  and M{\\'e}\n",
      "Found and included in lastname : and Ot{\\'a}\n",
      "Found and included in lastname : d Gonz{\\'a}\n",
      "Found and included in lastname :  Caliv{\\'a}\n",
      "Found and included in lastname : d Gonz{\\'a}\n",
      "Found and included in lastname :  Caliv{\\'a}\n",
      "Found and included in lastname : ={Kaji{\\'c}\n",
      "Found and included in lastname :  Sidib{\\'e}\n",
      "Found and included in lastname : gunovi{\\'c}\n",
      "Found and included in lastname : and Ot{\\'a}\n",
      "Found and included in lastname : d Gonz{\\'a}\n",
      "Found and included in lastname : nd Kov{\\'a}\n",
      "Found and included in lastname : and Gr{\\'o}\n",
      "Found and included in lastname :  and D{\\'e}\n",
      "Found and included in lastname : d Gonz{\\'a}\n",
      "Found and included in lastname :  and M{\\'e}\n",
      "Found and included in lastname :  Sidib{\\'e}\n",
      "Found and included in lastname : gunovi{\\'c}\n",
      "Found and included in lastname : gunovi{\\'c}\n",
      "Found and included in lastname :  and M{\\'a}\n",
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      "  title={Optical coherence tomography versus stereoscopic fundus photography or biomicroscopy for diagnosing diabetic macular edema: a systematic review},\n",
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      "}\n",
      "%\\RequirePackage{filecontents}\n",
      "%\\begin{filecontents*}{\\file.bib}\n",
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      "  author={Krolewski, AS and Warram, JH and Rand, LI and Christlieb, AR and Busick, EJ and Kahn, CR},\n",
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      "  year={2016},\n",
      "  publisher={IEEE}\n",
      "}\n",
      "@inproceedings{fu2016retinal,\n",
      "  title={Retinal vessel segmentation via deep learning network and fully-connected conditional random fields},\n",
      "  author={Fu, H and Xu, Y and Wong, DWK and Liu, J},\n",
      "  booktitle={Biomedical Imaging (ISBI), 2016 IEEE 13th International Symposium on},\n",
      "  pages={698--701},\n",
      "  year={2016}\n",
      "}\n",
      "@article{orlando2018ensemble,\n",
      "  title={An ensemble deep learning based approach for red lesion detection in fundus images},\n",
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      "  year={2018},\n",
      "  publisher={Elsevier}\n",
      "}\n",
      "@article{van2016fast,\n",
      "  title={Fast convolutional neural network training using selective data sampling: application to hemorrhage detection in color fundus images},\n",
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      "  journal={IEEE Transactions on Medical Imaging},\n",
      "  volume={35},\n",
      "  number={5},\n",
      "  pages={1273--1284},\n",
      "  year={2016},\n",
      "  publisher={IEEE}\n",
      "}\n",
      "@article{lam2018retinal,\n",
      "  title={Retinal lesion detection with deep learning using image patches},\n",
      "  author={Lam, C and Yu, C and Huang, L and Rubin, D},\n",
      "  journal={Investigative Ophthalmology \\& Visual Science},\n",
      "  volume={59},\n",
      "  number={1},\n",
      "  pages={590--596},\n",
      "  year={2018},\n",
      "  publisher={The Association for Research in Vision and Ophthalmology}\n",
      "}\n",
      "@article{abc,\n",
      "  title={A deep learning algorithm for prediction of age-related eye disease study severity scale for age-related macular degeneration from color fundus photography},\n",
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      "  journal={Ophthalmology},\n",
      "  volume={125},\n",
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      "  year={2018},\n",
      "  publisher={Elsevier}\n",
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      "@inproceedings{horta2017hybrid,\n",
      "  title={A Hybrid Approach for Incorporating Deep Visual Features and Side Channel Information with Applications to AMD Detection},\n",
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      "  booktitle={Machine Learning and Applications (ICMLA), 2017 16th IEEE International Conference on},\n",
      "  pages={716--720},\n",
      "  year={2017}\n",
      "}\n",
      "@article{burlina2017automated,\n",
      "  title={Automated grading of age-related macular degeneration from color fundus images using deep convolutional neural networks},\n",
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      "  journal={JAMA Ophthalmology},\n",
      "  volume={135},\n",
      "  number={11},\n",
      "  pages={1170--1176},\n",
      "  year={2017},\n",
      "  publisher={American Medical Association}\n",
      "}\n",
      "@article{burlina2017comparing,\n",
      "  title={Comparing humans and deep learning performance for grading AMD: A study in using universal deep features and transfer learning for automated AMD analysis},\n",
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      "  volume={82},\n",
      "  pages={80--86},\n",
      "  year={2017},\n",
      "  publisher={Elsevier}\n",
      "}\n",
      "@inproceedings{govindaiah2018deep,\n",
      "  title={Deep convolutional neural network based screening and assessment of age-related macular degeneration from fundus images},\n",
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      "  booktitle={Biomedical Imaging (ISBI 2018), 2018 IEEE 15th International Symposium on},\n",
      "  pages={1525--1528},\n",
      "  year={2018},\n",
      "  organization={IEEE}\n",
      "}\n",
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      "  author=\"Matsuba, S\n",
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      "and Ishitobi, N\n",
      "and Masumoto, H\n",
      "and Kiuchi, Y\",\n",
      "title=\"Accuracy of ultra-wide-field fundus ophthalmoscopy-assisted deep learning, a machine-learning technology, for detecting age-related macular degeneration\",\n",
      "journal=\"International Ophthalmology\",\n",
      "year=\"2019\",\n",
      "month=\"Jun\",\n",
      "day=\"01\",\n",
      "volume=\"39\",\n",
      "number=\"6\",\n",
      "pages=\"1269--1275\",\n",
      "abstract=\"To predict exudative age-related macular degeneration (AMD), we combined a deep convolutional neural network (DCNN), a machine-learning algorithm, with Optos, an ultra-wide-field fundus imaging system.\",\n",
      "issn=\"1573-2630\",\n",
      "doi=\"10.1007/s10792-018-0940-0\",\n",
      "url=\"https://doi.org/10.1007/s10792-018-0940-0\"\n",
      "}\n",
      "@article{tan2018age,\n",
      "  title={Age-related Macular Degeneration detection using deep convolutional neural network},\n",
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      "   Generation Computer Systems},\n",
      "  },\n",
      "  pages={127--135},\n",
      "  year={2018},\n",
      "  publisher={Elsevier}\n",
      "}\n",
      "@article{treder2018automated,\n",
      "  title={Automated detection of exudative age-related macular degeneration in spectral domain optical coherence tomography using deep learning},\n",
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      "  year={2018},\n",
      "  publisher={Springer}\n",
      "}\n",
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      "  year={2016}\n",
      "}\n",
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      "  year={2018},\n",
      "  publisher={Elsevier}\n",
      "}\n",
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      "  year={2017},\n",
      "  publisher={Elsevier}\n",
      "}\n",
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      "}\n",
      "@article{colas2016deep,\n",
      "  title={Deep learning approach for diabetic retinopathy screening},\n",
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      "  year={2018},\n",
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      "@article{esmaeelpour2011mapping,\n",
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      "}@article{regatieri2012choroidal,\n",
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      "@article{imamura2009enhanced,\n",
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      "  note = {Accessed: 2019-10-29}\n",
      "}\n",
      "@inproceedings{kurmann2019fused,\n",
      "  title={Fused Detection of Retinal Biomarkers in OCT Volumes},\n",
      "  author={Kurmann, T and M{\\'a}rquez-Neila, P and Yu, S and Munk, M and Wolf, S and Sznitman, R},\n",
      "  booktitle={International Conference on Medical Image Computing and Computer-Assisted Intervention},\n",
      "  pages={255--263},\n",
      "  year={2019},\n",
      "  organization={Springer}\n",
      "}\n",
      "@article{bhende2018optical,\n",
      "  title={Optical coherence tomography: A guide to interpretation of common macular diseases},\n",
      "  author={Bhende, M and Shetty, S and Parthasarathy, M K and Ramya, S},\n",
      "  journal={Indian journal of ophthalmology},\n",
      "  volume={66},\n",
      "  number={1},\n",
      "  pages={20},\n",
      "  year={2018},\n",
      "  publisher={Wolters Kluwer--Medknow Publications}\n",
      "}\n",
      "@misc{ps_oct,\n",
      "  title = {Polarization sensitive OCT},\n",
      "  howpublished = {\\url{https://zmpbmt.meduniwien.ac.at/wissenschaft-forschung/optical-imaging/functional-and-contrast-enhanced-imaging/polarization-sensitive-oct/}},\n",
      "  note = {Accessed: 2019-10-29}\n",
      "}\n",
      "@incollection{sherman1989history,\n",
      "  title={The history of the ophthalmoscope},\n",
      "  author={Sherman, S E},\n",
      "  booktitle={History of Ophthalmology},\n",
      "  pages={221--228},\n",
      "  year={1989},\n",
      "  publisher={Springer}\n",
      "}\n",
      "@article{venguibn,\n",
      "  title={Ibn al-Haytham: Founder of Physiological Optics?},\n",
      "  author={In:  R.Rashed, A V Lakshminarayanan},\n",
      "   Based Science: Technology and Sustainable Development},\n",
      "  },\n",
      "  number={1},\n",
      "  pages={63-108},\n",
      "  year={2017},\n",
      "  publisher={CRC Press,Boca raton, FL}\n",
      "}\n",
      "@article{kim2014convolutional,\n",
      "  title={Convolutional neural networks for sentence classification},\n",
      "  author={Kim, Y},\n",
      "  journal={arXiv preprint arXiv:1408.5882},\n",
      "  year={2014}\n",
      "}\n",
      "@inproceedings{nair2010rectified,\n",
      "  title={Rectified linear units improve restricted boltzmann machines},\n",
      "  author={Nair, V and Hinton, G E},\n",
      "  booktitle={Proceedings of the 27th international conference on machine learning (ICML-10)},\n",
      "  pages={807--814},\n",
      "  year={2010}\n",
      "}\n",
      "@incollection{hecht1992theory,\n",
      "  title={Theory of the backpropagation neural network},\n",
      "  author={Hecht-Nielsen, R},\n",
      "  booktitle={Neural networks for perception},\n",
      "  pages={65--93},\n",
      "  year={1992},\n",
      "  publisher={Elsevier}\n",
      "}\n",
      "@inproceedings{scherer2010evaluation,\n",
      "  title={Evaluation of pooling operations in convolutional architectures for object recognition},\n",
      "  author={Scherer, D and M{\\\"u}ll A and Behnke, S},\n",
      "  booktitle={International conference on artificial neural networks},\n",
      "  pages={92--101},\n",
      "  year={2010},\n",
      "  organization={Springer}\n",
      "}\n",
      "@inproceedings{szegedy2016rethinking,\n",
      "  title={Rethinking the inception architecture for computer vision},\n",
      "  author={Szegedy, C and Vanhoucke, V and Ioffe, S and Shlens, J and Wojna, Z},\n",
      "  booktitle={Proceedings of the IEEE conference on computer vision and pattern recognition},\n",
      "  pages={2818--2826},\n",
      "  year={2016}\n",
      "}\n",
      "@inproceedings{sengupta2019cross,\n",
      "  title={Cross-domain diabetic retinopathy detection using deep learning},\n",
      "  author={Sengupta, S and Singh, A and Zelek, J and Lakshminarayanan, V},\n",
      "  booktitle={Applications of Machine Learning},\n",
      "  volume={11139},\n",
      "  pages={111390V},\n",
      "  year={2019},\n",
      "  organization={International Society for Optics and Photonics}\n",
      "}\n",
      "@inproceedings{singh2019glaucoma,\n",
      "  title={Glaucoma diagnosis using transfer learning methods},\n",
      "  author={Singh, A and Sengupta, S and Lakshminarayanan, V},\n",
      "  booktitle={Applications of Machine Learning},\n",
      "  volume={11139},\n",
      "  pages={111390U},\n",
      "  year={2019},\n",
      "  organization={International Society for Optics and Photonics}\n",
      "}\n",
      "@inproceedings{gholami2018intra,\n",
      "  title={Intra-retinal segmentation of optical coherence tomography images using active contours with a dynamic programming initialization and an adaptive weighting strategy},\n",
      "  author={Gholami, P and Roy, P and Parthasarathy, M K and Ommani, A and Zelek, J and Lakshminarayanan, V},\n",
      "  booktitle={Optical Coherence Tomography and Coherence Domain Optical Methods in Biomedicine XXII},\n",
      "  volume={10483},\n",
      "  pages={104832M},\n",
      "  year={2018},\n",
      "  organization={International Society for Optics and Photonics}\n",
      "}`\n",
      "@article{cortes1995support,\n",
      "  title={Support-vector networks},\n",
      "  author={Cortes, C and Vapnik, V},\n",
      "  journal={Machine learning},\n",
      "  volume={20},\n",
      "  number={3},\n",
      "  pages={273--297},\n",
      "  year={1995},\n",
      "  publisher={Springer}\n",
      "}\n",
      "@article{liaw2002classification,\n",
      "  title={Classification and regression by randomForest},\n",
      "  author={Liaw, A and Wiener, M and others},\n",
      "   news},\n",
      "  },\n",
      "  number={3},\n",
      "  pages={18--22},\n",
      "  year={2002}\n",
      "}\n",
      "@article{sarle1994neural,\n",
      "  title={Neural networks and statistical models},\n",
      "  author={Sarle, W S},\n",
      "  year={1994},\n",
      "  publisher={Citeseer}\n",
      "}\n",
      "@article{fujimoto2016development,\n",
      "  title={The development, commercialization, and impact of optical coherence tomography},\n",
      "  author={Fujimoto, J and Swanson, E},\n",
      "  journal={Investigative ophthalmology \\& visual science},\n",
      "  volume={57},\n",
      "  number={9},\n",
      "  pages={OCT1--OCT13},\n",
      "  year={2016},\n",
      "  publisher={The Association for Research in Vision and Ophthalmology}\n",
      "}\n"
     ]
    }
   ],
   "source": [
    "new_data = \"\"\n",
    "i = 0\n",
    "while i < len(data): \n",
    "    \n",
    "    #stop a bit before the end, copy last 10 as is\n",
    "    if(i == len(data)-20):\n",
    "        new_data+=data[i:i+20]\n",
    "        #print(\"last few chars\" + data[i:i+20])\n",
    "        break\n",
    "        \n",
    "    # find all combinations of author part\n",
    "    if(data[i:i+8] == \"author={\" or data[i:i+10] == \"author = {\" or data[i:i+9] == \"author= {\" \n",
    "       or data[i:i+9] == \"author ={\"):\n",
    "        \n",
    "        #continue till the end bracket\n",
    "        while(data[i] != '}'):\n",
    "            \n",
    "                #put the spaces, \"and\", lastnames \n",
    "                while(data[i] != ',' and data[i] != '}'):\n",
    "                    new_data = new_data+data[i]\n",
    "                    #print(\"Inside author: \" + data[i])\n",
    "                    i+=1\n",
    "                \n",
    "                # for lastnames with chars like {\\'e}\n",
    "                    if(data[i] == '}' and data[i-4] == \"{\" and (data[i-2] == \"\\'\" or data[i-3] == \"\\'\")):\n",
    "                        new_data = new_data + data[i]\n",
    "                        print(\"Found and included in lastname : \" + data[i-10:i+1] )\n",
    "                        i+=1\n",
    "                \n",
    "                    elif(data[i] == '}'):\n",
    "                        #add the }\n",
    "                        new_data = new_data + data[i]\n",
    "                        #print(\"Closing braces:\" + data[i])\n",
    "                        i+=1\n",
    "                        break\n",
    "                        \n",
    "                #append comma\n",
    "                new_data = new_data+data[i]\n",
    "                #print(\"Comma: \" + data[i])\n",
    "                i+=1\n",
    "                \n",
    "                #add space after comma if there\n",
    "                \n",
    "                if(data[i] == ' '):\n",
    "                    new_data = new_data+data[i]\n",
    "                    #print(\"Space post comma: \" + data[i])\n",
    "                    i+=1\n",
    "            \n",
    "                # append the first letter of first name\n",
    "                new_data = new_data+data[i]\n",
    "                #print(\"First letter:\" + data[i])\n",
    "                i+=1\n",
    "                \n",
    "                #check if name was already shortened and had a middle name\n",
    "                # cuases error if first two letters of first name are caps\n",
    "                while(data[i] >= 'A' and data[i] <= 'Z'):\n",
    "                    new_data = new_data+data[i]\n",
    "                    #print(\"Already shortened middle name:\" + data[i])\n",
    "                    i+=1\n",
    "                \n",
    "                # skip rest of the characters of first name\n",
    "                while(data[i] != ' ' and data[i] != '}' ):\n",
    "                    #print(\"skipped: \" + data[i])\n",
    "                    i+=1\n",
    "                    \n",
    "                    # for firstnames with chars like {\\'e}\n",
    "                    if(data[i] == '}' and (data[i-4] == \"{\" or data[i-5] == \"{\") and (data[i-2] == \"\\'\" or data[i-3] == \"\\'\")):\n",
    "                        #new_data = new_data+data[i]\n",
    "                        #print(\"Found and skipped in first name: \" + data[i-4:i] )\n",
    "                        i+=1\n",
    "                    elif(data[i] == '}'):\n",
    "                        break\n",
    "                            \n",
    "            \n",
    "                \n",
    "                # append the space after first name if it exists and continue\n",
    "                if(data[i] == ' '):\n",
    "                    new_data = new_data+data[i]\n",
    "                    #print(\"space after first name\" + data[i])\n",
    "                    i+=1\n",
    "                \n",
    "                #check for middle name post the space after the first name\n",
    "                if(data[i:i+3] != 'and' and data[i] != '}'):\n",
    "                    #middle name exists, enter first char\n",
    "                    new_data = new_data+data[i]\n",
    "                    #print(\"First letter middle name:\" + data[i])\n",
    "                    i+=1                \n",
    "                    #check if middle name was pre shortened and had multiple caps => Mike, John AX\n",
    "                    # can cause issues\n",
    "                    while(data[i] >= 'A' and data[i] <= 'Z'):\n",
    "                        new_data = new_data+data[i]\n",
    "                        #print(\"Capital in shortened middle name:\" + data[i])\n",
    "                        i+=1\n",
    "                \n",
    "                    # skip rest of the characters of middle name\n",
    "                    while(data[i] != ' ' and data[i] != '}'):\n",
    "                        #print(\"skipped: \" + data[i])\n",
    "                        i+=1\n",
    "        \n",
    "    else:\n",
    "        new_data = new_data+data[i]\n",
    "        #print(\"Outside author:\" + data[i])\n",
    "        i+=1\n",
    "        \n",
    "print(new_data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "#destination\n",
    "with open(\"new.bib\", \"w\") as text_file:\n",
    "    text_file.write(new_data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
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