AI based Automatic Gating of B-Cells in Flow Cytometry

Abstract

Due to the extensive use of flow cytometry in immunophenotyping, cell sorting, cell cycle analysis, apoptosis, cell proliferation assays, intracellular calcium flux, and numerous other techniques in digital pathology, scientific research is convergent towards more robust and interpretable end-to-end solutions. Flow cytometry is a well-established method for the identification of cells in solution. It is most frequently employed to evaluate peripheral blood, bone marrow, and other body fluids. Whenever the source equipment for flow cytometry data collection is replaced, the features of the flow cytometry data change, offering a considerable challenge for existing learning-based algorithms. Automated gating utilising learning-based algorithms and automated logical parsing to manage significant challenges such signal overlap, poor signal detection, population segregation without overlaps, and other significant issues.