Title: | Reem Bashmail, Lamiaa A. Elrefaei, and Wadee Alhalabi, “Automatic Segmentation of Chromosome Cells”, In: Proceedings of the International Conference on Advanced Intelligent Systems and Informatics 2018. AISI 2018. Advances in Intelligent Systems and Computing, Vol. 845. Springer, Cham, p.654- 663. DOI:10.1007/978-3-319-99010-1_60 |
Authors: | Reem Bashmail, Lamiaa A. Elrefaei, and Wadee Alhalabi |
Year: | 2019 |
Keywords: | Not Available |
Journal: | International Conference on Advanced Intelligent Systems and Informatics 2018 |
Volume: | 845 |
Issue: | Not Available |
Pages: | 654-663 |
Publisher: | Springer, Cham |
Local/International: | International |
Paper Link: | |
Full paper | Not Available |
Supplementary materials | Not Available |
Abstract: |
Chromosome’s segmentation is an essential step in the automated chromosome classification system. It is important for chromosomes to be sep- arated from noise or background before the identification and classification. Chromosomes image (Metaphase) is generated in the third phase of mitosis. During metaphase, the cell’s chromosomes arrange themselves in the middle of the cell through a cellular. The analysis of metaphase chromosomes is one of the essential tools of cancer studies and cytogenetics. The Chromosomes are thickened and highly twisted in metaphase which make them very appropriate for visual analysis to determine the kind of each chromosome within the 24 classes (Chromosome karyotyping). This paper represents a chromosome seg- mentation method of high-resolution digitized metaphase images. Segmentation is done using Difference of Gaussian (DoG) as a sharpening filter before the classic technique (Otsu’s thresholding followed by morphological operations). The proposed method is tested using 130 metaphase images (6011 chromo- somes) provided by The Diagnostic Genomic Medicine Unit (DGMU) labora- tory at King Abdulaziz University. The experimental results show that the proposed method can successfully segment the metaphase chromosome images with 99.8% segmentation accuracy. |