Live-Cell Tracking Using SIFT Features in DIC Microscopic Videos
Data(s) |
01/09/2010
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Resumo |
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. |
Identificador | |
Idioma(s) |
eng |
Direitos |
info:eu-repo/semantics/restrictedAccess |
Fonte |
Jiang , R M , Crookes , D , Luo , N & Davidson , M W 2010 , ' Live-Cell Tracking Using SIFT Features in DIC Microscopic Videos ' IEEE Transactions on Biomedical Engineering , vol 57 , no. 9 , 5464333 , pp. 2219-2228 . DOI: 10.1109/TBME.2010.2045376 |
Palavras-Chave | #/dk/atira/pure/subjectarea/asjc/2200/2204 #Biomedical Engineering |
Tipo |
article |