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Proceedings Paper

Analysis of cancer cell morphology in fluorescence microscopy image exploiting shape descriptor
Author(s): Mi-Sun Kang; Hye-Ryun Kim; Sudong Kim; Gyu Ha Ryu; Myoung-Hee Kim
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Paper Abstract

Cancer cell morphology is closely related to their phenotype and activity. These characteristics are important in drug-response prediction for personalized cancer therapeutics. We used multi-channel fluorescence microscopy images to analyze the morphology of highly cohesive cancer cells. First, we detected individual nuclei regions in single-channel images using advanced simple linear iterative clustering. The center points of the nuclei regions were used as seeds for the Voronoi diagram method to extract spatial arrangement features from cell images. Human cancer cell populations form irregularly shaped aggregates, making their detection more difficult. We overcame this problem by identifying individual cells using an image-based shape descriptor. Finally, we analyzed the correlation between cell agglutination and cell shape.

Paper Details

Date Published: 6 April 2016
PDF: 6 pages
Proc. SPIE 9711, Imaging, Manipulation, and Analysis of Biomolecules, Cells, and Tissues IX, 97110O (6 April 2016); doi: 10.1117/12.2213829
Show Author Affiliations
Mi-Sun Kang, Ewha Womans Univ. (Korea, Republic of)
Hye-Ryun Kim, Ewha Womans Univ. (Korea, Republic of)
Sudong Kim, Samsung Electronics Co., Ltd. (Korea, Republic of)
Gyu Ha Ryu, School of Medicine, Sungkyunkwan Univ. (Korea, Republic of)
Myoung-Hee Kim, Ewha Womans Univ. (Korea, Republic of)

Published in SPIE Proceedings Vol. 9711:
Imaging, Manipulation, and Analysis of Biomolecules, Cells, and Tissues IX
Daniel L. Farkas; Dan V. Nicolau; Robert C. Leif, Editor(s)

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