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3d-attention-keras

This repo contains the 3D implementation of the commonly used attention mechanism for imaging.

3d-grad-cam

This repo contains Grad-CAM for 3D volumes.

augmented-volumetric-image-generator

Customised Keras' ImageDataGenerator for 3D volumetric medical image

brain-tissue-segmentation-using-deep-learning-pipeline-neuronet

This Repository is for the MISA Course final project which was Brain tissue segmentation. we adopt NeuroNet which is a comprehensive brain image segmentation tool based on a novel multi-output CNN architecture which has been trained and tuned using IBSR18 dataset

cerr

Matlab/Octave based platform for Radiological Research.

clam

Data-efficient and weakly supervised computational pathology on whole slide images - Nature Biomedical Engineering

cnn-hnscc

Deep learning based outcome modelling from CT scans of HNSCC patients

covid-19_prognosis

An artificial intelligence system for predicting the deterioration of COVID-19 patients in the emergency department

deepslide

Code for the Nature Scientific Reports paper "Pathologist-level classification of histologic patterns on resected lung adenocarcinoma slides with deep neural networks." A sliding window framework for classification of high resolution whole-slide images, often microscopy or histopathology images.

dl_radiomics_fusion

Comparison and fusion of deep learning and radiomics features of ground-glass nodules to predict the invasiveness risk of stage-I lung adenocarcinomas in CT scan

dnnsurv

easylearn_dev

Easylearn is designed for machine learning mainly in resting-state fMRI, radiomics and other fields (such as EEG). Easylearn is built on top of scikit-learn, pytorch and other packages. Easylearn can assist doctors and researchers who have limited coding experience to easily realize machine learning, e.g., (MR/CT/PET/EEG)imaging-marker- or other biomarker-based disease diagnosis and prediction, treatment response prediction, disease subtyping, dimensional decoding for transdiagnostic psychiatric diseases or other diseases, disease mechanism exploration and etc.

escc_ml

Deep-learning Radiomics for Classification Modelling

external-attention-pytorch

🍀 Pytorch implementation of various Attention Mechanisms, MLP, Re-parameter, Convolution, which is helpful to further understand papers.⭐⭐⭐

fastmoe

A fast MoE impl for PyTorch

gbc

keras-resnet3d

Implementations of ResNets for volumetric data, including a vanilla resnet in 3D.

m3d-cam

main

mcpcounter

medicalnet

Many studies have shown that the performance on deep learning is significantly affected by volume of training data. The MedicalNet project provides a series of 3D-ResNet pre-trained models and relative code.

mmoe

nnet-survival

Discrete-Time Survival Model for Neural Networks

nnunet-onwindows

un nnUnet on Windows

nnunetlearnonwindows

paddlevit

:robot: PaddleViT: State-of-the-art Visual Transformer and MLP Models for PaddlePaddle 2.0+

pathology-images-analysis-using-cnn

Comprehensive analysis of lung cancer pathology images to discover tumor shape and boundary features that predict survival outcome.

pdac_recurrence_prediction

python_for_microscopists

https://www.youtube.com/channel/UC34rW-HtPJulxr5wp2Xa04w?sub_confirmation=1

pytorch-mixture-of-experts

using deepspeed to build a distributed mixture of experts model