Science Score: 54.0%

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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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    Links to: sciencedirect.com
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    Low similarity (8.9%) to scientific vocabulary
Last synced: 10 months ago · JSON representation ·

Repository

Basic Info
  • Host: GitHub
  • Owner: schwobr
  • License: gpl-3.0
  • Language: Python
  • Default Branch: master
  • Size: 8.99 MB
Statistics
  • Stars: 1
  • Watchers: 1
  • Forks: 1
  • Open Issues: 0
  • Releases: 0
Created about 4 years ago · Last pushed over 1 year ago
Metadata Files
Readme License Citation

README.md

HEnorm

This repository contains the official implementation of Bias reduction using combined stain normalization and augmentation for AI-based classification of histological images. This code was tested with python 3.7 and softwares listed in requirements. In order to use it, please install required dependencies by running: bash pip install -r requirements.txt

AugmentHE

AugmentHE was implemented using the albumentations interface. It can be easily used within a PyTorch dataset: ```python class MyDataset(Dataset): def init(self, imagepaths): super().init() self.imagepaths = image_paths self.aug = StainAugmentor()

def __len__(self):
    return len(self.image_paths)

def __getitem__(self, idx):
    img = load_image(self.image_paths[idx])
    augmented_img = self.aug(image=img)["image"]
    return augmented_img

```

HEnorm

HEnorm was implemented using PyTorch and fastai's DynamicUnet. To reproduce the papers' model, simply write: python model = Normalizer("cgr_5_32_4")

You can then train this model using a reference dataset and AugmentHE.

You can also use our pretrained weights on $1024 \times 1024$ images at level 1 $(0.5 \mu m/px)$. python norm = torch.jit.load("norm_1024_1.pt").eval() x_norm = norm(x) # x must be a tensor of shape [n, c, h, w]

Transforms

All set of transforms described in the paper can be found in transforms.py.

Owner

  • Login: schwobr
  • Kind: user

Citation (CITATION.cff)

cff-version: 1.2.0
message: "If you use this software, please cite it as below."
authors:
- family-names: "Franchet"
  given-names: "Camille"
  orcid: "https://orcid.org/0000-0002-3214-0142 "
- family-names: "Schwob"
  given-names: "Robin"
  orcid: "https://orcid.org/0000-0002-0811-1982"
- family-names: "Bataillon"
  given-names: "Guillaume"
  orcid: "https://orcid.org/ 0000-0003-2013-1668"
- family-names: "Syrykh"
  given-names: "Charlotte"
  orcid: "https://orcid.org/ 0000-0002-3201-6109"
- family-names: "Péricart"
  given-names: "Sarah"
  orcid: "https://orcid.org/0000-0001-8148-2950"
- family-names: "Frénois"
  given-names: "François-Xavier"
  orcid: "https://orcid.org/0000-0002-8433-7764"
- family-names: "Penault-Llorca"
  given-names: "Frédérique"
  orcid: "https://orcid.org/0000-0002-4279-5492"
- family-names: "Lacroix-Triki"
  given-names: "Magali"
  orcid: "https://orcid.org/0000-0002-6641-8536"
- family-names: "Arnould"
  given-names: "Laurent"
  orcid: "https://orcid.org/0000-0001-6133-1362"
- family-names: "Lemonnier"
  given-names: "Jérôme"
  orcid: "https://orcid.org/0000-0002-8821-2168"
- family-names: "Alliot"
  given-names: "Jean-Marc"
  orcid: "https://orcid.org/0000-0003-4858-3500"
- family-names: "Filleron"
  given-names: "Thomas"
  orcid: "https://orcid.org/0000-0003-0724-0659"
- family-names: "Brousset"
  given-names: "Pierre"
  orcid: "https://orcid.org/0000-0002-8629-3291"
title: "Bias reduction using combined stain normalization and augmentation for AI-based classification of histological images"
version: 1.0.0
doi: 10.5281/zenodo.1234
date-released: 2022-07-19
url: "https://github.com/schwobr/HEnorm"
preferred-citation:
  type: article
  authors:
  - family-names: "Franchet"
    given-names: "Camille"
    orcid: "https://orcid.org/0000-0002-3214-0142 "
  - family-names: "Schwob"
    given-names: "Robin"
    orcid: "https://orcid.org/0000-0002-0811-1982"
  - family-names: "Bataillon"
    given-names: "Guillaume"
    orcid: "https://orcid.org/ 0000-0003-2013-1668"
  - family-names: "Syrykh"
    given-names: "Charlotte"
    orcid: "https://orcid.org/ 0000-0002-3201-6109"
  - family-names: "Péricart"
    given-names: "Sarah"
    orcid: "https://orcid.org/0000-0001-8148-2950"
  - family-names: "Frénois"
    given-names: "François-Xavier"
    orcid: "https://orcid.org/0000-0002-8433-7764"
  - family-names: "Penault-Llorca"
    given-names: "Frédérique"
    orcid: "https://orcid.org/0000-0002-4279-5492"
  - family-names: "Lacroix-Triki"
    given-names: "Magali"
    orcid: "https://orcid.org/0000-0002-6641-8536"
  - family-names: "Arnould"
    given-names: "Laurent"
    orcid: "https://orcid.org/0000-0001-6133-1362"
  - family-names: "Lemonnier"
    given-names: "Jérôme"
    orcid: "https://orcid.org/0000-0002-8821-2168"
  - family-names: "Alliot"
    given-names: "Jean-Marc"
    orcid: "https://orcid.org/0000-0003-4858-3500"
  - family-names: "Filleron"
    given-names: "Thomas"
    orcid: "https://orcid.org/0000-0003-0724-0659"
  - family-names: "Brousset"
    given-names: "Pierre"
    orcid: "https://orcid.org/0000-0002-8629-3291"
  doi: "10.0000/00000"
  journal: "npj Digital Medicine"
  month: 9
  start: 1 # First page number
  end: 10 # Last page number
  title: "Bias reduction using combined stain normalization and augmentation for AI-based classification of histological images"
  issue: 1
  volume: 1
  year: 2022

GitHub Events

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Dependencies

requirements.txt pypi
  • albumentations ==1.1.0
  • nptyping ==1.4.4
  • numpy ==1.21.2
  • spams ==2.6.3
  • staintools ==2.1.2
  • timm ==0.5.4
  • torch ==1.10.1