Computer Science – Computer Vision and Pattern Recognition
Scientific paper
2011-12-18
Computer Science
Computer Vision and Pattern Recognition
Submitted to IEEE Transaction on Biomedical Engineering
Scientific paper
Chromosome segmentation is a fundamental task in human chromosome analysis. Most of previous methods for separation between touching chromosomes require human intervention. In this paper, a geometry based method is used for automatic chromosome segmentation. This method can be divided into two phases. In the first phase, chromosome clusters are detected using three geometric criteria and in the second phase chromosome clusters are separated using a proper cut line. However, most earlier methods do not work well with chromosome clusters that contain more than two chromosomes. Our method, on the other hand, has a high efficiency in separation of chromosome clusters in such scenarios. Another advantage of the proposed method is that it can easily apply to any type of images such as binary images. This is due to the fact that the proposed scheme uses the geometric features of chromosomes which are independent of the type of images. The performance of the proposed scheme is demonstrated on a database containing touching and partially overlapping chromosomes with a success rate of over 91%.
Fotouhi Mehran
Khalaj Babak Hossein
Minaee Shervin
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