Earticle

This paper proposes Multidirectional Block Ranking based segmentation and removal of Interphase cells from chromosome images. The efficiency of automatic karyotyping decreases with the presence of undivided, condensed mass of chromosomes called Interphase cells, stain, debris and other unwanted interferences in the chromosome image. The algorithm segments and removes these interferences and enhances the accuracy of automatic karyotyping. The method is tested and excellent segmentation accuracy is accomplished. The chromosome image is preprocessed and a boundary-mapping algorithm is applied to identify the Region of Interest (RoI). The image is divided into blocks and ranks are assigned to all the blocks using Gaussian Ranking Functions (GRF) based on their contribution to the RoI. A higher rank is assigned to the block contributing more while a lesser rank is assigned to other blocks that contribute less to the RoI. The Interphase cells that constitute the RoI are removed from the chromosome images based on the cumulative rank obtained by the blocks in the chromosome image. The proposed algorithm is applied to segment and remove Interphase cells, stains, dirt and other particles that exhibit structural homogeneity. The algorithm gives accurate results in applications where the RoI to be segmented share the grey level with the background wherein the traditional image segmentation methods fall short of accomplishing precise segmentation results.