Jessejx

Self-supervised-method-for-Melanoma-Segmentation

JIANet: Jigsaw-Invariant Self-supervised Learning of Auto-encoder Based Reconstruction for Melanoma Segmentation

R2D2-GAN

‘‘R2D2-GAN: Robust Dual-Discriminator Generative Adversarial Network for Microscopy Hyperspectral Image Super-Resolution,’’ submitted to IEEE TRANSACTIONS ON MEDICAL IMAGING

TSNE-UMAP-Embedding-Visualisation

A Simple and easy to use way to Visualise Embeddings!

2021-AAAI-CC

Code for the paper "Contrastive Clustering" (AAAI 2021)

2DUnet-trail

Unet2d for brats segmentation.

3D-MRI-brain-tumor-segmentation-using-autoencoder-regularization

Pytorch implementation of the paper "3D MRI brain tumor segmentation using autoencoder regularization" by Myronenko A. [https://arxiv.org/abs/1810.11654]

albumentations

Fast image augmentation library and an easy-to-use wrapper around other libraries. Documentation: https://albumentations.ai/docs/ Paper about the library: https://www.mdpi.com/2078-2489/11/2/125

Augmentor3D

A module for 3D image augmentations for deep learning, specifically medical images such as CT, MRI.

awesome-self-supervised-learning

A curated list of awesome self-supervised methods

BraTs

PyTorch & Keras implementation for BraTs (Brain Tumor Segmentation)

Jesse-Lab

brats_segmentation-pytorch

3d unet + vae, repoduce brats2018 winner solution

deepcluster

Deep Clustering for Unsupervised Learning of Visual Features

disentangling-vae

Experiments for understanding disentanglement in VAE latent representations

External-Attention-pytorch

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

flexible-yolov5

More readable and flexible yolov5 with more backbone(resnet, shufflenet, moblienet )

Jessejx

Config files for my GitHub profile.

med2image

Converts medical images to more displayable formats, e.g. NIfTI to jpg.

medicaldetectiontoolkit

The Medical Detection Toolkit contains 2D + 3D implementations of prevalent object detectors such as Mask R-CNN, Retina Net, Retina U-Net, as well as a training and inference framework focused on dealing with medical images.

memae

Memorizing Normality to Detect Anomaly: Memory-augmented Deep Autoencoder for Unsupervised Anomaly Detection (MemAE)

memAE-Pytorch

Memory-augmented Deep Autoencoder (https://arxiv.org/abs/1904.02639) for Vector Data

pacnet

Pixel-Adaptive Convolutional Neural Networks (CVPR '19)

Pigmented-skin-lesions-classification

在投图象图形学报论文的代码

Pretext-Invariant-Representations

Implementation of the paper Self-Supervised Learning of Pretext-Invariant Representations

pytorch-unet-resnet-50-encoder

standard-readme

A standard style for README files

Unet-Segmentation-Pytorch-Nest-of-Unets

Implementation of different kinds of Unet Models for Image Segmentation - Unet , RCNN-Unet, Attention Unet, RCNN-Attention Unet, Nested Unet

vae_iop

pytorch implementation for "Variational Autoencoder with Implicit Optimal Priors".