M-FISH Karyotyping - A New Approach Based on Watershed Transform

TL;DR

This paper introduces an automated M-FISH chromosome segmentation method using watershed transform and naive Bayes classification, achieving improved accuracy in karyotyping for genetic analysis.

Contribution

It presents a novel watershed-based segmentation approach combined with classification and post-processing to enhance M-FISH chromosome analysis accuracy.

Findings

Achieved 84.21% accuracy on 40 images

Improved segmentation accuracy over pixel-by-pixel methods

Effective re-classification reduces misclassification

Abstract

Karyotyping is a process in which chromosomes in a dividing cell are properly stained, identified and displayed in a standard format, which helps geneticist to study and diagnose genetic factors behind various genetic diseases and for studying cancer. M-FISH (Multiplex Fluorescent In-Situ Hybridization) provides color karyotyping. In this paper, an automated method for M-FISH chromosome segmentation based on watershed transform followed by naive Bayes classification of each region using the features, mean and standard deviation, is presented. Also, a post processing step is added to re-classify the small chromosome segments to the neighboring larger segment for reducing the chances of misclassification. The approach provided improved accuracy when compared to the pixel-by-pixel approach. The approach was tested on 40 images from the dataset and achieved an accuracy of 84.21 %.