Enhanced Kinetochore Detection During Mitotic Human Cell Division using CFAR

In this paper, we present an innovative application of the Constant False Alarm Rate (CFAR) algorithm, traditionally utilized in radar signal processing, to enhance the accuracy and reliability of kinetochore (KT) tracking in live-cell lattice light-sheet microscopy (LLSM) imaging of human cells during the mitotic phase of cell division. Fluorescently labelled KTs appear as spots in diffraction-limited light microscopy. Traditional KT detection methods, such as adaptive thresholding, often struggle with the dynamic and noisy backgrounds of cells, leading to less efficient KT identification. By adapting the CFAR algorithm to the specific challenges of $K T$ detection in 3D, we present a method that offers improved precision and stability in detecting KTs across different stages of mitosis. The performance of the CFAR-KT method was rigorously compared to the adaptive thresholding approach across a cohort of 31 cells, with results highlighting CFAR-KT’s enhanced detection efficiency. Despite a slightly lower mean detection count compared to the adaptive method, the CFAR-KT method achieved lower false positives and a higher success rate in tracking KTs over the duration of the cell division process, underscoring its effectiveness in capturing the dynamics of KTs.