DeeperHistReg: Robust Whole Slide Images Registration Framework
Marek Wodzinski, Niccol\`o Marini, Manfredo Atzori, Henning M\"uller

TL;DR
DeeperHistReg is a versatile software framework that enables robust registration of large, multi-stain whole slide images through preprocessing, alignment, and nonrigid registration, supporting multiple algorithms and high resolutions.
Contribution
It introduces an extensible framework that integrates state-of-the-art registration algorithms for multi-stain WSIs, supporting arbitrary resolutions and easy integration of new methods.
Findings
Supports registration of WSIs up to 200k x 200k resolution
Provides an extensible interface for multiple registration algorithms
Available as a Python package and Docker container
Abstract
DeeperHistReg is a software framework dedicated to registering whole slide images (WSIs) acquired using multiple stains. It allows one to perform the preprocessing, initial alignment, and nonrigid registration of WSIs acquired using multiple stains (e.g. hematoxylin \& eosin, immunochemistry). The framework implements several state-of-the-art registration algorithms and provides an interface to operate on arbitrary resolution of the WSIs (up to 200k x 200k). The framework is extensible and new algorithms can be easily integrated by other researchers. The framework is available both as a PyPI package and as a Docker container.
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Taxonomy
TopicsMedical Image Segmentation Techniques · Advanced Neural Network Applications · Medical Imaging and Analysis
