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3d-augmentation-techniques

Chechink the performance of different augmentation techniques on the BraTS 2020 data.

agnet

The code of "Attention Guided Network for Retinal Image Segmentation" in MICCAI 2019

ce-net

The manuscript has been accepted in TMI.

deep-learning-for-image-processing

deep learning for image processing including classification and object-detection etc.

machine-learning-homework

Matlab Coding homework for Machine Learning

mmsegmentation

OpenMMLab Semantic Segmentation Toolbox and Benchmark.

ms-dropblock

Retinal Vessel Segmentation Based on Multi-Shape DropBlock Approach

neural-doodle

Turn your two-bit doodles into fine artworks with deep neural networks, generate seamless textures from photos, transfer style from one image to another, perform example-based upscaling, but wait... there's more! (An implementation of Semantic Style Transfer.)

pam-unet

squeeze_and_excitation

PyTorch Implementation of 2D and 3D 'squeeze and excitation' blocks for Fully Convolutional Neural Networks

swin-transformer

This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows".

swin-unet

The codes for the work "Swin-Unet: Unet-like Pure Transformer for Medical Image Segmentation"

two-stage-vae-attention-gate-brats2020

2SCM-VAAG: A Two-Stage Cascade Model with Variational Autoencoders and Attention Gates for MRI Brain Tumor Segmentation (BraTS 2020 Challenge; BrainLes2020 paper)