AutoMorph 2022 👀
--Code for AutoMorph: Automated Retinal Vascular Morphology Quantification via a Deep Learning Pipeline.
Please contact ykzhoua@gmail.com or yukun.zhou.19@ucl.ac.uk if you have questions.
Project website: https://rmaphoh.github.io/projects/automorph.html
Talks on NIHR Moorfields BRC: https://moorfieldsbrc.nihr.ac.uk/case-study/research-report/
News 👀
2023-08-24 update: Added feature measurement for disc-centred images; removed unused files in M3 folders.
Pixel resolution
The units for vessel average width, disc/cup height and width, and calibre metrics are defined as microns. For it, we need to organise a resolution_information.csv which includes the pixel resolution information, which can be queried in FDA or Dicom files. Alternatively, some people use approximate value for every images, e.g., 0.008 for Topcon 3D-OCT.
If you don't use these features or care their units, you can just run following command after putting all images in the folder of ./images
python generate_resolution.py
Running AutoMorph
Running with Colab
Use the Google Colab and a free Tesla T4 gpu Colab link click.
Running on local/virtual machine
Install and use on your own machines LOCAL.md.
Running with Docker
Zero experience in Docker? No worries DOCKER.md.
Common questions
Memory/ram error
We use Tesla T4 (16Gb) and 32vCPUs (120Gb). When you meet memory/ram issue in running, try to decrease batch size:
- ./M1_Retinal_Image_quality_EyePACS/test_outside.sh -b=64 to smaller, e.g., 32 or 16.
- ./M2_Artery_vein/test_outside.sh --batch-size=8 to smaller
- ./M2_lwnet_disc_cup/test_outside.sh --batchsize=8 to smaller
Invalid results
In csv files, invalid values (e.g., optic disc segmentation failure) are indicated with -1.
Components
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Vessel segmentation BF-Net
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Image pre-processing EyeQ
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Optic disc segmentation lwnet
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Feature measurement retipy
Citation
@article{zhou2022automorph,
title={AutoMorph: Automated Retinal Vascular Morphology Quantification Via a Deep Learning Pipeline},
author={Zhou, Yukun and Wagner, Siegfried K and Chia, Mark A and Zhao, An and Xu, Moucheng and Struyven, Robbert and Alexander, Daniel C and Keane, Pearse A and others},
journal={Translational vision science \& technology},
volume={11},
number={7},
pages={12--12},
year={2022},
publisher={The Association for Research in Vision and Ophthalmology}
}