Track and predict the energy consumption and carbon footprint of training deep learning models.

Self-Supervised Learning in PyTorch

The MAMA-MIA Dataset: A Multi-Center Breast Cancer DCE-MRI Public Dataset with Expert Segmentations

🐍 Geometric Computer Vision Library for Spatial AI

PyTorch implementation of the U-Net for image semantic segmentation with high quality images

nnDetection is a self-configuring framework for 3D (volumetric) medical object detection which can be applied to new data sets without manual intervention. It includes guides for 12 data sets that …

PyTorch Lightning + Hydra. A very user-friendly template for ML experimentation. ⚡🔥⚡

Notebooks for working with The Cancer Imaging Archive datasets. Have you written one? Submit a PR!

A Quick Guide on Radiology Image Pre-processing for Deep Learning Applications in Prostate Cancer Research

UniverSeg: Universal Medical Image Segmentation

[MedIA 2023] The official implementation of MIA paper "Dive into the details of Self-supervised Learning for Medical Image Analysis"

MONAI Tutorials

Paper bank for Self-Supervised Learning

A curated list of awesome self-supervised methods

This repository is mainly dedicated for listing the recent research advancements in the application of Self-Supervised-Learning in medical images computing field