An algorithm for overlapping chromosome segmentation based on region selection

Chromosome images are commonly used in karyotype analysis to diagnose chromosomal diseases. However, there are often chromosome adhesion and overlaps in chromosome images, so effective chromosome segmentation is conducive to smooth karyotype analysis. To date, some progress has been made in automatic chromosome segmentation, and existing methods can be used to segment overlapping chromosomes in most cases. However, when two or more overlapping regions are too close to each other in the image of overlapping chromosomes, the existing segmentation methods adjust the non-overlapping regions that do not belong to the overlapping region, resulting in incomplete segmentation of chromatids. Therefore, we use a heuristic algorithm to solve this problem from the point of view of mathematics and geometry to improve the segmentation of overlapping chromosomes. Starting from chromosome images, the existing problems and solutions are explained and displayed in the way of visualized interpretable image features, which helps to better understand the algorithm. Our method achieves 92.86% splicing accuracy and 90.44% overall segmentation accuracy on open datasets. The experimental results show that our method can effectively improve the problem of incorrect chromosome segmentation when two or more overlapping parts of overlapping chromosomes are too close to each other. It can accelerate the development of artificial intelligence in computational pathology and provide patients with more accurate medical services.