wuusn

wuusn's Stars

• facebookresearch/dinov2

  PyTorch code and models for the DINOv2 self-supervised learning method.

  Language:Jupyter Notebook9.5k96411850

• hojonathanho/diffusion

  Denoising Diffusion Probabilistic Models

  Language:Python4k2022382

• MouseLand/cellpose

  a generalist algorithm for cellular segmentation with human-in-the-loop capabilities

  Language:Jupyter Notebook1.4k29920410

• microsoft/SimMIM

  This is an official implementation for "SimMIM: A Simple Framework for Masked Image Modeling".

  Language:Python935234288

• CellProfiler/CellProfiler

  An open-source application for biological image analysis

  Language:Python931453.3k383

• optuna/optuna-examples

  Examples for https://github.com/optuna/optuna

  Language:Python703875177

• prov-gigapath/prov-gigapath

  Prov-GigaPath: A whole-slide foundation model for digital pathology from real-world data

  Language:Python448611262

• webermarcolivier/statannot

  add statistical annotations (pvalue significance) on an existing boxplot generated by seaborn boxplot

  Language:Jupyter Notebook396105874

• mahmoodlab/UNI

  Towards a general-purpose foundation model for computational pathology - Nature Medicine

  Language:Jupyter Notebook36874553

• mahmoodlab/CONCH

  A vision-language foundation model for computational pathology - Nature Medicine

  Language:Python29331923

• purnasai/Dino_V2

  Dino V2 for Classification, PCA Visualization, Instance Retrival: https://arxiv.org/abs/2304.07193

  Language:Jupyter Notebook1733511

• MECLabTUDA/Lifelong-nnUNet

  Language:Python13711316

• instanseg/instanseg

  Language:Python12831619

• yang-ruixin/PyTorch-Image-Models-Multi-Label-Classification

  Multi-label classification based on timm.

  Language:Jupyter Notebook1133212

• mahmoodlab/SISH

  Fast and scalable search of whole-slide images via self-supervised deep learning - Nature Biomedical Engineering

  Language:Python1004726

• DIAGNijmegen/pathology-whole-slide-data

  A package for working with whole-slide data including a fast batch iterator that can be used to train deep learning models.

  Language:Python9663827

• DIAGNijmegen/HoVer-UNet

  Language:Python35336

• cvlab-stonybrook/SAMPath

  Repository for "SAM-Path: A Segment Anything Model for Semantic Segmentation in Digital Pathology" (MedAGI2023, MICCAI2023 workshop)

  Language:Python337297

• AI4SCR/VirtualMultiplexer

  A generative toolkit to translate H&E images to multiplexed IHC

  Language:Jupyter Notebook30412

• choosehappy/HoverFast

  Blazing fast nuclei segmentation for brightfield Whole Slide Images

  Language:Jupyter Notebook29544

• fuscc-deep-path/sc_MTOP

  sc-MTOP is an analysis framework based on deep learning and computational pathology. This framework aims to characterize the tumor ecosystem diversity at the single-cell level. This code provide 1) Hover-Net-based nuclear segmentation and classification; 2) Nuclear morphological and texture feature extraction; 3) Multi-level pairwise nuclear graph construction and spatial topological feature extraction.

  Language:Python283116

• secrierlab/HistoMIL

  A Python package for handling histopathology whole-slide images using multiple instance learning (MIL) techniques.

  Language:Python28227

• impromptuRong/hd_wsi

  Language:JavaScript27243

• LooKing9218/UIOS

  Language:Python26105

• CielAl/torch-staintools

  Pytorch-adaptation of GPU-accelerated StainTool's stain normalization algorithms

  Language:Python23234

• benbergner/ips

  PyTorch Implementation of Iterative Patch Selection for High-Resolution Image Recognition

  Language:Python17311

• DIAGNijmegen/nnUNet-for-pathology

  Adapted nnUNet framework with additional features to suit the requirements for pathology applications

  Language:Python11105

• brunettsp/myosothes

  An automated Myofibers Segmentation wOrkflow Tuned for HE Staining

  Language:Groovy42

• burtonrj/consensusclustering

  Python implementation of Consensus Clustering by Monti et al. (2003)

  Language:Python40

• cgtuebingen/DualQueryMIL

  Dual-Query Multiple Instance Learning for Dynamic Meta-Embedding based Tumor Classification

  Language:Python370