Title: Improving segmentation of 3D touching cell nuclei using flow tracking on surface meshes

Authors: Gang Li; Lei Guo

Addresses: School of Automation, Northwestern Polytechnical University, Xi'an 710072, China. ' School of Automation, Northwestern Polytechnical University, Xi'an 710072, China

Abstract: Automatic segmentation of touching cell nuclei in 3D microscopy images is of great importance in bioimage informatics and computational biology. This paper presents a novel method for improving 3D touching cell nuclei segmentation. Given binary touching nuclei by the method in Li et al. (2007), our method herein consists of several steps: surface mesh reconstruction and curvature information estimation; direction field diffusion on surface meshes; flow tracking on surface meshes; and projection of surface mesh segmentation to volumetric images. The method is validated on both synthesised and real 3D touching cell nuclei images, demonstrating its validity and effectiveness.

Keywords: 3D cell nuclei segmentation; surface flow tracking; surface field diffusion; image segmentation; surface mesh reconstruction; curvature information estimation; touching cell nuclei.

DOI: 10.1504/IJCBDD.2012.045952

International Journal of Computational Biology and Drug Design, 2012 Vol.5 No.1, pp.66 - 74

Received: 08 May 2021
Accepted: 12 May 2021

Published online: 16 Mar 2012 *

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