Python package for dealing with whole slide images (.svs) for machine learning, particularly for fast prototyping. Includes patch sampling and storing using OpenSlide. Patches may be stored in LMDB, HDF5 files, or to disk. It is highly recommended to fork and download this repository so that personal customisations can be made for your work.
A deep learning approach to predicting breast tumor proliferation scores for the TUPAC16 challenge
SCGV is an interactive graphical tool for single-cell genomics data, with emphasis on single-cell genomics of cancer
A library for training deep neural networks using pathology data by accessing patches on-the-fly
A pyqt5 widget for viewing collection of whole-slide images with Openslide
GUI frontend for OpenSlides web server used by openslides-portable for OpenSlides 2.x
Digital pathology image viewer with support for human/machine generated annotations and markups.
Source code corresponding to the blog article: 指纹识别源代码(1)-图像处理 指纹识别源代码(2)-特征点提取