A collection of resources on applications of Transformers in Medical Imaging.

BOA is a segmentation tool of CT scans by the SHIP-AI group (https://ship-ai.ikim.nrw/). Combining the TotalSegmentator and the Body Composition Analysis, this tool is capable of analyzing medical …

This repository is for the first comprehensive survey on Meta AI's Segment Anything Model (SAM).

The largest collection of PyTorch image encoders / backbones. Including train, eval, inference, export scripts, and pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (V…

Semantic segmentation models with 500+ pretrained convolutional and transformer-based backbones.

Easy-to-use image segmentation library with awesome pre-trained model zoo, supporting wide-range of practical tasks in Semantic Segmentation, Interactive Segmentation, Panoptic Segmentation, Image …

OpenMMLab Semantic Segmentation Toolbox and Benchmark.

A collection of loss functions for medical image segmentation

The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.

Image augmentation for machine learning experiments.

Fast and flexible image augmentation library. Paper about the library: https://www.mdpi.com/2078-2489/11/2/125