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Reference code for the paper: Deep White-Balance Editing (CVPR 2020). Our method is a deep learning multi-task framework for white-balance editing.
A curated list of awesome C (or C) frameworks, libraries, resources, and shiny things. Inspired by awesome-... stuff.
[arXiv '24] Efficient Cell Nuclei Instance Segmentation with Large Convolution Kernels
Fast and scalable search of whole-slide images via self-supervised deep learning - Nature Biomedical Engineering
NuInsSeg: A Fully Annotated Dataset for Nuclei Instance Segmentation in H&E-Stained Histological Images
Medical image retrieval using SOAT feature extractor
This is the official PyTorch implementation of Structure Embedded Nucleus Classification for Histopathology Images
Cell Graph Transformer for Nuclei Classification, AAAI 2024
cGAN-based Multi Organ Nuclei Segmentation
A GPU-accelerated library containing highly optimized building blocks and an execution engine for data processing to accelerate deep learning training and inference applications.
RandStainNA: Simple and efficient augmentations for histology [MICCAI 2022]
Lightning fast C /CUDA neural network framework
Image augmentation for machine learning experiments.
Source code for paper: https://arxiv.org/pdf/2305.17370.pdf
Self-Supervised Vision Transformers Learn Visual Concepts in Histopathology (LMRL Workshop, NeurIPS 2021)
Prov-GigaPath: A whole-slide foundation model for digital pathology from real-world data
List of pathology feature extractors and foundation models
A coding-free framework built on PyTorch for reproducible deep learning studies. 🏆25 knowledge distillation methods presented at CVPR, ICLR, ECCV, NeurIPS, ICCV, etc are implemented so far. 🎁 Train…
[CVPR 2024] Dynamic Graph Representation with Knowledge-aware Attention for Histopathology Whole Slide Image Analysis
DAS-MIL: Distilling Across Scales for MILClassification of Histological WSIs