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av-analysis-svm

AV Analysis to enhance DR classifications using Support Vector Machine (SVM)

ava-net

Deep Learning for Arterial-Venous-Area (AVA) Segmentation using OCTA images with Python and TensorFlow.

cfz-net-training

Deep Learning for Capillary Free Zones (CFZ) Segmentation using OCTA Images with Python and PyTorch.

clip

CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image

cmsc-segmentation

Segmentation of Corneal Mesenchymal Stem Cells (CMSC) in microscopic images using OpenCV

digital-pathology-segmentation

Cell Nuclei Instance Segmentation on Cancer Instance Segmentation (PanNuke) Dataset Using Python and PyTorch.

mansour2002

mcat

Multimodal Co-Attention Transformer for Survival Prediction in Gigapixel Whole Slide Images

multimodal-avnet

Deep learning AV classification in OCT and OCTA using Python and TensorFlow.

nnunet

openslide-python

Python bindings to OpenSlide

pytorch-image-models

PyTorch image models, scripts, pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (ViT), MobileNet-V3/V2, RegNet, DPN, CSPNet, Swin Transformer, MaxViT, CoAtNet, ConvNeXt, and more

random-forest-classifier-rfc

Random Forest Classifier (RFC) for Artery-Vein (AV) Analysis to increase Diabetic Retinopathy (DR) binary and multiclass classifications

segmentation_models.pytorch

Segmentation models with pretrained backbones. PyTorch.

semantic-segmentation

Nvidia Semantic Segmentation monorepo

slideflow

Deep learning library for digital pathology, with both Tensorflow and PyTorch support.

svm-sfs-classification

Support Vector Machine (SVM) and Sequential Forward Selection (SFS) for CLV Analysis in binary and multiclass classifications in Python using Scikit-learn and MLxtend.

tmi2022

A graph-transformer for whole slide image classification

transformers-for-cis

SegFormer, a Transformer-Based Model, for Cell Nuclei Instance Segmentation on PanNuke Dataset Using PyTorch

vit-pytorch

Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch