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Proceedings Paper

Determining the number of clusters for nuclei segmentation in breast cancer image
Author(s): Chastine Fatichah; Dini Adni Navastara; Nanik Suciati; Lubna Nuraini
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Paper Abstract

Clustering is commonly technique for image segmentation, however determining an appropriate number of clusters is still challenging. Due to nuclei variation of size and shape in breast cancer image, an automatic determining number of clusters for segmenting the nuclei breast cancer is proposed. The phase of nuclei segmentation in breast cancer image are nuclei detection, touched nuclei detection, and touched nuclei separation. We use the Gram-Schmidt for nuclei cell detection, the geometry feature for touched nuclei detection, and combining of watershed and spatial k-Means clustering for separating the touched nuclei in breast cancer image. The spatial k-Means clustering is employed for separating the touched nuclei, however automatically determine the number of clusters is difficult due to the variation of size and shape of single cell breast cancer. To overcome this problem, first we apply watershed algorithm to separate the touched nuclei and then we calculate the distance among centroids in order to solve the over-segmentation. We merge two centroids that have the distance below threshold. And the new of number centroid as input to segment the nuclei cell using spatial k- Means algorithm. Experiment show that, the proposed scheme can improve the accuracy of nuclei cell counting.

Paper Details

Date Published: 8 February 2017
PDF: 7 pages
Proc. SPIE 10225, Eighth International Conference on Graphic and Image Processing (ICGIP 2016), 102252E (8 February 2017); doi: 10.1117/12.2266980
Show Author Affiliations
Chastine Fatichah, Institut Teknologi Sepuluh Nopember (Indonesia)
Dini Adni Navastara, Institut Teknologi Sepuluh Nopember (Indonesia)
Nanik Suciati, Institut Teknologi Sepuluh Nopember (Indonesia)
Lubna Nuraini, Institut Teknologi Sepuluh Nopember (Indonesia)


Published in SPIE Proceedings Vol. 10225:
Eighth International Conference on Graphic and Image Processing (ICGIP 2016)
Yulin Wang; Tuan D. Pham; Vit Vozenilek; David Zhang; Yi Xie, Editor(s)

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