Enhanced Rotated Mask R-CNN for Chromosome Segmentation

Abstract

Karyotyping is an important process for finding chromosome abnormalities that could cause genetic disorders. This process first requires cytogeneticists to arrange each chromosome from the metaphase image to generate the karyogram. In this process, chromosome segmentation plays an important role and it is directly related to whether the karyotyping can be achieved. The key to achieving accurate chromosome segmentation is to effectively segment the multiple touching and overlapping chromosomes at the same time identify the isolated chromosomes. This paper proposes a method named Enhanced Rotated Mask R-CNN for automatic chromosome segmentation and classification. The Enhanced Rotated Mask R-CNN method can not only accurately segment and classify the isolated chromosomes in metaphase images but also effectively alleviate the problem of inaccurate segmentation for touching and overlapping chromosomes. Experiments show that the proposed approach achieves competitive performances with 49.52 AP on multi-class evaluation and 69.96 AP on binary-class evaluation for chromosome segmentation.