Live-Cell Tracking Using SIFT Features in DIC Microscopic Videos

Jiang, Richard, Crookes, Danny, Luo, Nie and Davidson, Michael W. (2010) Live-Cell Tracking Using SIFT Features in DIC Microscopic Videos. IEEE Transactions on Biomedical Engineering, 57 (9). pp. 2219-2228. ISSN 0018-9294

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Abstract

In this paper, a novel motion-tracking scheme using scale-invariant features is proposed for automatic cell motility analysis in gray-scale microscopic videos, particularly for the live-cell tracking in low-contrast differential interference contrast (DIC) microscopy. In the proposed approach, scale-invariant feature transform (SIFT) points around live cells in the microscopic image are detected, and a structure locality preservation (SLP) scheme using Laplacian Eigenmap is proposed to track the SIFT feature points along successive frames of low-contrast DIC videos. Experiments on low-contrast DIC microscopic videos of various live-cell lines shows that in comparison with principal component analysis (PCA) based SIFT tracking, the proposed Laplacian-SIFT can significantly reduce the error rate of SIFT feature tracking. With this enhancement, further experimental results demonstrate that the proposed scheme is a robust and accurate approach to tackling the challenge of live-cell tracking in DIC microscopy.

Item Type:	Article
Subjects:	G400 Computer Science
Department:	Faculties > Engineering and Environment > Computer and Information Sciences
Depositing User:	Ellen Cole
Date Deposited:	07 May 2013 08:01
Last Modified:	13 Oct 2019 00:30
URI:	http://nrl.northumbria.ac.uk/id/eprint/12484

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