Resolving phenotyping discordance with SPACEMAP, an integrated machine learning framework.

ABSTRACT: Multiplex imaging technologies have revolutionized our ability to study cellular behavior within the tissue microenvironment. Translating this complex data into meaningful biological insights requires a unified analytical framework. To address this, we developed SPACEMAP (Spatial Phenotyping And Classification with Enhanced Multiplex Analysis Pipeline), a comprehensive Python and Qupath-based platform for multiplex imaging analysis. SPACEMAP integrates image registration, segmentation, artifact removal, tissue and zone classification, spatial feature extraction, and a consolidated phenotyping approach into a single system. A core feature of SPACEMAP is its high-fidelity phenotyping. To evaluate classification performance, we benchmark

SUBMITTER: Dawod B 

PROVIDER: S-EPMC12707289 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature