A machine learning approach to automate microinfarct and microhemorrhage screening in hematoxylin and eosin-stained human brain tissues.

ABSTRACT: Microinfarcts and microhemorrhages are characteristic lesions of cerebrovascular disease. Although multiple studies have been published, there is no one universal standard criteria for the neuropathological assessment of cerebrovascular disease. In this study, we propose a novel application of machine learning in the automated screening of microinfarcts and microhemorrhages. Utilizing whole slide images (WSIs) from postmortem human brain samples, we adapted a patch-based pipeline with convolutional neural networks. Our cohort consisted of 22 cases from the University of California Davis Alzheimer's Disease Research Center brain bank with hematoxylin and eosin-stained formalin-fixed, paraffin-embedded sections across 3 anatomical areas: frontal, parietal, and occipital lobes (40 WSIs with m

SUBMITTER: Cerny Oliveira L 

PROVIDER: S-EPMC11747222 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature