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Live-Cell Tracking Using SIFT Features in DIC Microscopic Videos

Research output: Contribution to Journal/Magazine › Journal article › peer-review

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Live-Cell Tracking Using SIFT Features in DIC Microscopic Videos. / Jiang, Richard M.; Crookes, Danny; Luo, Nie et al.
In: IEEE Transactions on Biomedical Engineering, Vol. 57, No. 9, 09.2010, p. 2219-2228.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Harvard

Jiang, RM, Crookes, D, Luo, N & Davidson, MW 2010, 'Live-Cell Tracking Using SIFT Features in DIC Microscopic Videos', IEEE Transactions on Biomedical Engineering, vol. 57, no. 9, pp. 2219-2228. https://doi.org/10.1109/TBME.2010.2045376

APA

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, 57(9), 2219-2228. https://doi.org/10.1109/TBME.2010.2045376

Vancouver

Jiang RM, Crookes D, Luo N, Davidson MW. Live-Cell Tracking Using SIFT Features in DIC Microscopic Videos. IEEE Transactions on Biomedical Engineering. 2010 Sept;57(9):2219-2228. doi: 10.1109/TBME.2010.2045376

Author

Jiang, Richard M. ; Crookes, Danny ; Luo, Nie et al. / Live-Cell Tracking Using SIFT Features in DIC Microscopic Videos. In: IEEE Transactions on Biomedical Engineering. 2010 ; Vol. 57, No. 9. pp. 2219-2228.

Bibtex

@article{8407bf4263a94210b5f5de476c0f547a,
title = "Live-Cell Tracking Using SIFT Features in DIC Microscopic Videos",
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.",
keywords = "Laplacian eigenmap, live-cell motion tracking, microscopic cell imaging, principal component analysis (PCA), scale-invariant feature transform (SIFT)",
author = "Jiang, {Richard M.} and Danny Crookes and Nie Luo and Davidson, {Michael W.}",
year = "2010",
month = sep,
doi = "10.1109/TBME.2010.2045376",
language = "English",
volume = "57",
pages = "2219--2228",
journal = "IEEE Transactions on Biomedical Engineering",
issn = "0018-9294",
publisher = "IEEE Computer Society",
number = "9",

}

RIS

TY - JOUR

T1 - Live-Cell Tracking Using SIFT Features in DIC Microscopic Videos

AU - Jiang, Richard M.

AU - Crookes, Danny

AU - Luo, Nie

AU - Davidson, Michael W.

PY - 2010/9

Y1 - 2010/9

N2 - 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.

AB - 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.

KW - Laplacian eigenmap

KW - live-cell motion tracking

KW - microscopic cell imaging

KW - principal component analysis (PCA)

KW - scale-invariant feature transform (SIFT)

U2 - 10.1109/TBME.2010.2045376

DO - 10.1109/TBME.2010.2045376

M3 - Journal article

VL - 57

SP - 2219

EP - 2228

JO - IEEE Transactions on Biomedical Engineering

JF - IEEE Transactions on Biomedical Engineering

SN - 0018-9294

IS - 9

ER -