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Official pytorch implementation of Paper - 🍝 PASTA: Pathology-Aware MRI to PET Cross-modal Translation with Diffusion Models - MICCAI 2024
Efficient and comprehensive pytorch implementation of NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis from Mildenhall et al. 2020.
Code for the paper "Test-time adaptable neural networks for robust medical image segmentation"
CArdiac SegmenTation with cOnstRaints (CASTOR) project
[CIBM 2024] Segment Anything Model for Medical Image Segmentation: Open-Source Project Summary
Semi Supervised Learning for Medical Image Segmentation, a collection of literature reviews and code implementations.
Try to use the SAM-ViT as the backbone to create the learnable prompt for semantic segmentation
[CVPR 2023] Explicit Visual Prompting for Low-Level Structure Segmentations
DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.
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.
Segmentation of Corneal Endothelium Images with U-Net
A collection of papers about Transformer in the field of medical image analysis.
[CVPR 2023] DepGraph: Towards Any Structural Pruning
Image augmentation for machine learning experiments.
A framework for data augmentation for 2D and 3D image classification and segmentation
PyTorch implementation of 'Squeeze and Excite' Guided Few Shot Segmentation of Volumetric Scans
a generalist algorithm for cellular segmentation with human-in-the-loop capabilities
Implementation of Hausdorff loss function for DNN learning in segmentation tasks.
Pytorch implementation of convolutional neural network visualization techniques
This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows".
TMI 2018. H-DenseUNet: Hybrid Densely Connected UNet for Liver and Tumor Segmentation from CT Volumes
Lung fields segmentation on CXR images using convolutional neural networks.
Implementation of the Swin Transformer in PyTorch.
[CVPR 2021] Rethinking Semantic Segmentation from a Sequence-to-Sequence Perspective with Transformers
Visualizing CNN filters using PyTorch
The largest collection of PyTorch image encoders / backbones. Including train, eval, inference, export scripts, and pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (V…
This is a PyTorch re-implementation of Axial-DeepLab (ECCV 2020 Spotlight)