An Automated Pipeline for Differential Cell Counts on Whole-Slide Bone Marrow Aspirate Smears.

ABSTRACT: The pathologic diagnosis of bone marrow disorders relies in part on the microscopic analysis of bone marrow aspirate (BMA) smears and the manual counting of marrow nucleated cells to obtain a differential cell count (DCC). This manual process has significant limitations, including the analysis of only a small subset of optimal slide areas and nucleated cells, as well as interobserver variability due to differences in cell selection and classification. To address these shortcomings, we developed an automated machine learning-based pipeline for obtaining 11-component DCCs on whole-slide BMAs. This pipeline uses a sequential process of identifying optimal BMA regions with high proportions of marrow nucleated cells, detecting individual cells within these optimal areas, and classifying these c

SUBMITTER: Lewis JE 

PROVIDER: S-EPMC10310355 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature