/AI-in-Medical-Imaging

Primary LanguagePython

Along with this github project, this page will also be updated

https://www.notion.so/ideasandexecution/a7aba15ec65948f9a3d0a04da2f2d0d0?v=426eca156f7a4824b0f8f8504f1c4bcd

Image Analysis

https://petebankhead.gitbooks.io/imagej-intro/content/

MRI - Brain Tumor

Frameworks

http://www.niftynet.io/#features
https://cmiclab.cs.ucl.ac.uk/CMIC/NiftyNet/

MRI basics

https://www.youtube.com/watch?v=CKbemQBAzUE

This is a very good class on dicom and nifti preprocessing
https://www.coursera.org/learn/neurohacking

what is nifti affine:
http://nipy.org/nibabel/coordinate_systems.html

nifti affine usage:
https://www.programcreek.com/python/example/98177/nibabel.Nifti1Image

sitk image tutorial notebooks:
https://insightsoftwareconsortium.github.io/SimpleITK-Notebooks/Python_html/03_Image_Details.html

https://blog.dataversioncontrol.com/best-practices-of-orchestrating-python-and-r-code-in-ml-projects-f28f3a879484

a good website to find usage examples:
https://www.programcreek.com/python/example/96382/SimpleITK.WriteImage

pyradiomics notebook:
https://www.radiomics.io/pyradiomicsnotebook.html

Neuroscience software

The best slicer software: https://www.slicer.org/
http://neuro.debian.net/
https://miykael.github.io/nipype-beginner-s-guide/installation.html
https://miykael.github.io/nipype_tutorial/
https://github.com/nilearn/nilearn

Data

https://www.smir.ch/
https://wiki.cancerimagingarchive.net/display/DOI/Segmentation+Labels+and+Radiomic+Features+for+the+Pre-operative+Scans+of+the+TCGA-GBM+collection
https://wiki.cancerimagingarchive.net/display/DOI/TCIA+Analysis+Results

Dicom / Nifti Preprocessing

https://github.com/mingrui/mri_modality_classification_deep_learning

Segmentation

https://github.com/Kamnitsask/deepmedic
https://github.com/zsdonghao/u-net-brain-tumor
https://github.com/ellisdg/3DUnetCNN
https://github.com/fabianbormann/Tensorflow-DeconvNet-Segmentation
https://github.com/naldeborgh7575/brain_segmentation
https://github.com/e271141/BRATS
https://github.com/kaspermarstal/BrainNet
https://github.com/jocicmarko/ultrasound-nerve-segmentation
https://github.com/pietz/brats-segmentation
https://github.com/GUR9000/Deep_MRI_brain_extraction
https://github.com/cvdlab/nn-segmentation-for-lar

Resources

https://github.com/desimone/segmentation-models
https://github.com/madlymissyou/deep-learning-for-neuroimage
https://github.com/jindongwang/transferlearning
https://github.com/dformoso/machine-learning-mindmap
https://github.com/mnielsen/neural-networks-and-deep-learning
https://github.com/GUR9000/Deep_MRI_brain_extraction
https://github.com/Radiomics/pyradiomics
https://github.com/nipy/niwidgets

WSI - Pathology Image

Computational Pathology Basics

https://www.youtube.com/watch?v=sxkDzbtIJ5g

Similar Problems

https://www.kaggle.com/c/planet-understanding-the-amazon-from-space/data
https://blog.deepsense.ai/deep-learning-for-satellite-imagery-via-image-segmentation/
https://vooban.com/en/tips-articles-geek-stuff/satellite-image-segmentation-workflow-with-u-net/
https://github.com/alexander-rakhlin/ICIAR2018#method
https://computationalpathologygroup.github.io/ASAP/#home

Data

https://camelyon17.grand-challenge.org/data/

Tools

https://github.com/Peter554/StainTools
https://bmi.stonybrookmedicine.edu/node/535

Models

https://github.com/CODAIT/deep-histopath

Hardware

https://github.com/Microsoft/pai

Genome

Secure, Private, Distributed computing https://github.com/mingrui/secure-gwas