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<aside> ๐ฌ PathScribe is a cross-platform software for viewing, annotation and automatic analysis of histological images, including whole slide images. PathScribe can be used for both educational and scientific purposes.
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PathScribe is a multi-platform client-server application that allows to efficiently work with whole slide images of any size without having to download them to your device. PathScribe implements an adaptive and modern interface that allows to comfortably work with histological images, both on a desktop computer or laptop, and on mobile devices (tablets, smartphones) with touch screens.
The following platforms are currently supported:
PathScribe requires an active Internet connection to work. The bandwidth requirements are minimal, even mobile Internet can be used.
As part of PathScribe we developed its own universal format for storing histological images .psi, as well as a converter that allows to convert popular image formats to .psi for comfortable viewing and working inside PathScribe. Another feature of the converter is a set of compression algorithms focused on working with histological images, which allow reducing the size of an image in .psi format compared to the original one up to several times, which reduces the amount of files stored on the server, and also speeds up the client part of the application.
The converter currently supports the following image formats:
PathScribe is intended for use in the educational process when teaching a pathological anatomy course. PathScribe software will allow students to quickly and conveniently access large educational collections of histological images over the Internet without having to download data to the device. Each image of the educational collection is accompanied by a text description and group of tags. Tags allow to filter the list of images in educational collection.
PathScribe is developed to be used for academic and research purposes. The implementation of a set of algorithms developed by our team for accelerated annotating, classification, segmentation, analysis and search by the content of histological images using modern neural network approaches in PathScribe will allow this software to become a universal assistant for histologists, significantly speeding up and automating their interaction with histological images. These options are under development.