Automatic Segmentation of Human Chromosomes

Abstract

Abstract-This paper is concerned with automatic segmentation of high resolution digitized metaphases. Firstly using a thresholding technique, a binary image of the cell picture is obtained. This binary image contains the addresses of darker pixels of the gray image of the colored cell picture. Several thousand of random points are assigned from among these addresses, and then using a distance condition, typically 50 pixels, and the number of centers is reduced to near 100. These points are search centers for chromosome segmentation. Algorithm first searches eight pixels surrounding the center. Picks the coordinates of the pixels darker than the gray level 0.9, then passes to one of the pixels recently recorded as dark enough, and repeat the same procedure to the neighbors which are not visited before. If none of the new neighbors are not darker than 0.9, search reaches at the boundaries of the chromosome, and ends. Then we call the pixels of the chromosomes in the colored image from the addresses in the binary counterparts to finish segmentation.

Statistical Karyotype Analysis Using CNN and Geometric Optimization

“…Sharma et al [1] used crowdsourcing to segment out the chromosomes and represented a method to evaluate the results. Many approaches based on the heuristic rules and geometry are also represented, such as [5]- [7]. But they had low robustness under the clinic conditions, where the shapes and distribution of chromosomes usually vary greatly.…”

Machine Learning Classifiers Evaluation for Automatic Karyogram Generation from G-Banded Metaphase Images

“…Nowadays, there are no public databases of karyotypes images or systems to automatically build karyograms using this technique. The computer-based automatic construction of karyograms performs two complementary and sequential tasks: image segmentation and segmented chromosomes classification [30,31]. There are several works that segment and classify Q-band chromosomes images with varying results [8,26,32,33].…”

“…It is important to define the optimal chromosome features to obtain a good accuracy. In the literature, shape description, length, centromere position, and the banding pattern have been used as chromosomes descriptors [12,18,30,31,[34][35][36]. In Reference [8,33], the authors annotate that these characteristics are useful to determine if the chromosome was correctly segmented, but they can not be used as the only descriptors of the chromosome.…”