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November 19, 2023

UNSEG: unsupervised segmentation of cells and their nuclei in complex tissue samples

B. Kochetov, P. Bell, P. S. Garcia, A. S. Shalaby, R. Raphael, B. Raymond, B. J. Leibowitz, K. Schoedel, R. M. Brand, R. E. Brand, J. Yu, L. Zhang, B. Diergaarde, R. E. Schoen, A. Singhi, S. Uttam

BioRxiv preprint. Manuscript is under review.

New work from our lab pushes forward the performance limits of unsupervised methods in the difficult task of segmenting cells and their nuclei in tissue samples in the context of immunofluorecense imaging and its highly multiplexed counterpart. As part of UNSEG, we have a developed a new perturbed watershed method that stabilizes and improves classical watershed performance for segmenting clustered nuclei.