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HEST: Bringing Spatial Transcriptomics and Histopathology together - NeurIPS 2024 (Spotlight)
Blazing fast nuclei segmentation for brightfield Whole Slide Images
H&E tailored Randaugment: automatic data augmentation policy selection for H&E-stained histopathology.
QuPath extension to work with WSInfer - https://wsinfer.readthedocs.io/
A large, multi-domain mitotic Figure Dataset
NuInsSeg: A Fully Annotated Dataset for Nuclei Instance Segmentation in H&E-Stained Histological Images
Dataset of 9536 H&E-stained patches for colorectal polyps classification and adenomas grading | ICIP21 https://doi.org/10.1109/ICIP42928.2021.9506198
QuPath extension for Segment Anything Model (SAM)
Large Scale Non maximum Suppression. This project implements a O(nlog(n)) approach for non max suppression, useful for object detection ran on very large images such as satellite or histology, when…
Repository for "Gigapixel Whole-Slide Images Classification using Locally Supervised Learning"
Hierarchical Image Pyramid Transformer - CVPR 2022 (Oral)
Use this to download all elements of the BCSS dataset described in: Amgad M, Elfandy H, ..., Gutman DA, Cooper LAD. Structured crowdsourcing enables convolutional segmentation of histology images. …
Sparse Convolutional Context-Aware Multiple Instance Learning for Whole Slide Image Classification | https://arxiv.org/abs/2105.02726
An open-source digital pathology based rapid image annotation tool
A standardized Python API with necessary preprocessing, machine learning and explainability tools to facilitate graph-analytics in computational pathology.
Over 200 figures and diagrams of the most popular deep learning architectures and layers FREE TO USE in your blog posts, slides, presentations, or papers.
Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.
Open source tools for computational pathology - Nature BME
Pretrained model for self supervised histopathology
Scalene: a high-performance, high-precision CPU, GPU, and memory profiler for Python with AI-powered optimization proposals
Usable Implementation of "Bootstrap Your Own Latent" self-supervised learning, from Deepmind, in Pytorch