Full package for applying deep learning to virtual slides.

Tools for whole slide image (WSI) processing. Especially for (pairwise) patch extraction, annotation parsing and data preparation for deep learning purposes.

Simple library for preprocessing histopathological whole-slide images (WSI) into tiles (a.k.a. patches) towards deep learning

🔬 Syntax - the arrangement of whole-slide-images and their image tiles to create well-formed computational pathology pipelines.

A pyqt5 widget for viewing whole-slide images with Openslide

Preprocessing module for large histological images

🔬 Python SDK providing access to the Aignostics Platform. Includes Aignostics Launchpad (Desktop Application), Aignostics CLI (Command-Line Interface), example notebooks, and Aignostics Client Library.

A library for training deep neural networks using pathology data by accessing patches on-the-fly

GIANT-style WSI navigation env plus MultiPathQA eval runner. Plug in any VLM, zoom with bboxes, log trajectories, and score accuracy.

Big Image Python Library

A pyqt5 widget for viewing collection of whole-slide images with Openslide

Convenient interface for generating tiles from Aperio SVS format images

A pyqt5 GUI for CBIR in whole-slide images with Openslide

Digital Open-source pathology tool based on OpenSlide with Manipulation & annotations feature.

Use the openslide Library to process the WSI image

🛠️ Simplify DICOM handling with this unified toolkit featuring CLIs and utilities in multiple languages for effective data management and processing.