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Quantitative tracking of tumor cells in phase-contrast microscopy exploiting halo artifact pattern

Title
Quantitative tracking of tumor cells in phase-contrast microscopy exploiting halo artifact pattern
Authors
Kang M.-S.Song S.-M.Lee H.Kim M.-H.
Ewha Authors
김명희
SCOPUS Author ID
김명희scopus
Issue Date
2012
Journal Title
Progress in Biomedical Optics and Imaging - Proceedings of SPIE
ISSN
1605-7422JCR Link
Citation
Progress in Biomedical Optics and Imaging - Proceedings of SPIE vol. 8317
Indexed
SCOPUS scopus
Document Type
Conference Paper
Abstract
Tumor cell morphology is closely related to its invasiveness characteristics and migratory behaviors. An invasive tumor cell has a highly irregular shape, whereas a spherical cell is non-metastatic. Thus, quantitative analysis of cell features is crucial to determine tumor malignancy or to test the efficacy of anticancer treatment. We use phase-contrast microscopy to analyze single cell morphology and to monitor its change because it enables observation of long-term activity of living cells without photobleaching and phototoxicity, which is common in other fluorescence-labeled microscopy. Despite this advantage, there are image-level drawbacks to phase-contrast microscopy, such as local light effect and contrast interference ring, among others. Thus, we first applied a local filter to compensate for non-uniform illumination. Then, we used intensity distribution information to detect the cell boundary. In phase-contrast microscopy images, the cell normally appears as a dark region surrounded by a bright halo. As the halo artifact around the cell body is minimal and has an asymmetric diffusion pattern, we calculated the cross-sectional plane that intersected the center of each cell and was orthogonal to the first principal axis. Then, we extracted the dark cell region by level set. However, a dense population of cultured cells still rendered single-cell analysis difficult. Finally, we measured roundness and size to classify tumor cells into malignant and benign groups. We validated segmentation accuracy by comparing our findings with manually obtained results. © 2012 SPIE.
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DOI
10.1117/12.911683
ISBN
9780819489661
Appears in Collections:
엘텍공과대학 > 컴퓨터공학과 > Journal papers
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