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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
- 김명희
- Issue Date
- 2012
- Journal Title
- Progress in Biomedical Optics and Imaging - Proceedings of SPIE
- ISSN
- 1605-7422
- Citation
- Progress in Biomedical Optics and Imaging - Proceedings of SPIE vol. 8317
- Indexed
- 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.
- DOI
- 10.1117/12.911683
- ISBN
- 9780819489661
- Appears in Collections:
- 인공지능대학 > 컴퓨터공학과 > Journal papers
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