eyepy_extended
Science Score: 54.0%
This score indicates how likely this project is to be science-related based on various indicators:
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✓CITATION.cff file
Found CITATION.cff file -
✓codemeta.json file
Found codemeta.json file -
✓.zenodo.json file
Found .zenodo.json file -
○DOI references
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✓Academic publication links
Links to: zenodo.org -
○Academic email domains
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○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (12.9%) to scientific vocabulary
Repository
Basic Info
- Host: GitHub
- Owner: kennedybacelar
- License: mit
- Language: Python
- Default Branch: master
- Size: 12.6 MB
Statistics
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
- Releases: 0
Metadata Files
README.md
eyepy
Use Python to import, analyse and visualize retinal imaging data.
The eyepy python package provides a simple interface to import and process OCT volumes. Everything you import with one of our import functions becomes an EyeVolume object which provides a unified interface to the data. The EyeVolume object provides methods to plot the localizer (fundus) image and B-scans as well as to compute and plot quantifications of voxel annotations such as drusen. Check out the documentation, especially the Cookbook chapter, for more information.
Features
- Import Data (Heyex-E2E, Heyex-VOL, Heyex-XML, Topcon-FDA, B-Scan collections, RETOUCH Challenge, AMD Dataset from Duke University)
- Analyze OCT volumes (compute and quantify drusen)
- Visualize OCT volumes with annotations and quantifications
- Save and load EyeVolume objects
Getting Started
Installation
Attention: If you want to use a version prior to 0.12.0 you have to install from the eyepie name instead. This is because we used eyepie as a package name on PyPI until the previous owner of the eyepy name on PyPI was so kind to transfer it to us.
To install the latest version of eyepy run pip install -U eyepy. (It is eyepie for versions < 0.12.0)
Getting Started
When you don't hava a supported OCT volume at hand you can check out our sample dataset to get familiar with eyepy.
python
from eyepy.data import load
ev = load("drusen_patient")
If you have data at hand use one of eyepys import functions.
```python
Import HEYEX E2E export
ev = ep.importheyexe2e("path/to/file.e2e")
Import HEYEX XML export
ev = ep.importheyexxml("path/to/folder")
Import HEYEX VOL export
ev = ep.importheyexvol("path/to/file.vol")
Import Topcon FDA export
ev = ep.importtopconfda("path/to/file.fda")
Import volume from Duke public dataset
ev = ep.importdukemat("path/to/file.mat")
Import volume form RETOUCH challenge
ev = ep.importretouch("path/to/volumefolder") ```
Related Projects:
- OCT-Converter: Extract raw optical coherence tomography (OCT) and fundus data from proprietary file formats. (.fds/.fda/.e2e/.img/.oct/.dcm)
- eyelab: A GUI for annotation of OCT data based on eyepy
- Projects by the Translational Neuroimaging Laboratory
- UOCTE Unofficial continuation of https://bitbucket.org/uocte/uocte
- OCTAnnotate
- heyexReader
- OCTExplorer Iowa Reference Algorithm
Owner
- Name: Kennedy Bacelar
- Login: kennedybacelar
- Kind: user
- Location: Salvador/Bahia - Brazil
- Repositories: 7
- Profile: https://github.com/kennedybacelar
Citation (CITATION.cff)
# This CITATION.cff file was generated with cffinit.
# Visit https://bit.ly/cffinit to generate yours today!
cff-version: 1.2.0
title: eyepy
message: >-
If you use this software, please cite it using the
metadata from this file.
type: software
authors:
- given-names: Olivier
family-names: Morelle
email: oli4morelle@gmail.com
orcid: 'https://orcid.org/0000-0001-6404-2726'
affiliation: >-
University of Bonn - Bonn-Aachen International
Center for Information Technology (b-it) /
University Hospital Bonn - Department of
Ophthalmology
identifiers:
- type: url
value: 'https://github.com/MedVisBonn/eyepy/tree/v0.12.0'
repository-code: 'https://github.com/MedVisBonn/eyepy/tree/v0.12.0'
abstract: >-
Eye imaging data from different device vendors
often come in different file formats. Additionally,
public datasets often have their own way of storing
data for distribution. The lack of documentation
for many device-specific formats is a problem
already when working with a single data source
while the pure amount of different formats slows
down everyone trying to use data from multiple
sources.
This Python package aims at providing a unified
interface to a wide variety of eye imaging formats
and the execution of standard tasks such as data
visualization and quantification on ETDRS grids.
Thereby, it enables the development of
device-independent software and algorithms.
keywords:
- OCT
- Drusen
- Heidelberg
- HEYEX
- ETDRS
license: MIT
version: v0.12.0
date-released: '2022-03-02'