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

Full text not available from this repository. (Request a copy)
Official URL: http://dx.doi.org/10.1109/TBME.2010.2045376

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 Science and Digital Technologies
Depositing User: Ellen Cole
Date Deposited: 07 May 2013 08:01
Last Modified: 10 Aug 2015 11:24
URI: http://nrl.northumbria.ac.uk/id/eprint/12484

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year

View more statistics


Policies: NRL Policies | NRL University Deposit Policy | NRL Deposit Licence