Stitching and registering highly multiplexed whole-slide images of tissues and tumors using ASHLAR.

ABSTRACT:

Motivation

Stitching microscope images into a mosaic is an essential step in the analysis and visualization of large biological specimens, particularly human and animal tissues. Recent approaches to highly multiplexed imaging generate high-plex data from sequential rounds of lower-plex imaging. These multiplexed imaging methods promise to yield precise molecular single-cell data and information on cellular neighborhoods and tissue architecture. However, attaining mosaic images with single-cell accuracy requires robust image stitching and image registration capabilities that are not met by existing methods.

Results

We describe the development and testing of ASHLAR, a Python tool for coordinated stitching and registration of 103 or more individual multiplexed images to generat

SUBMITTER: Muhlich JL 

PROVIDER: S-EPMC9525007 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature