Mohammadreza Yazdchi

Work place: Department of Biomedical Engineering, University of Isfahan, Isfahan, Iran



Research Interests: Medical Image Computing, Image Processing, Image Manipulation, Image Compression, Medical Informatics


Mohammadreza Yazdchi obtained his B.Sc. in Electrical Engineering from the Isfahan University of Technology in 1997. He received his M.Sc. and Ph.D. in Biomedical Engineering from Amirkabir University of Technology in 2000 and 2006, respectively. He is currently an Assistant Professor in the Department of Biomedical Engineering at the University of Isfahan since 2007. His research interests include Biomedical Signal Processing, Medical Image Processing, Biomedical Instrumentation, Biologically Inspired Computing and Bio-Inspired Engineering.

Author Articles
Using Shape Information and Dark Paths for Automatic Recognition of Touching and Overlapping Chromosomes in G-Band Images

By Payman Moallem Arezoo Karimizadeh Mohammadreza Yazdchi

DOI:, Pub. Date: 28 Apr. 2013

Nowadays, Karyotype analysis is frequently used in cytogenetics. It is a time-consuming and repetitive work therefore an automatic analysis can greatly be valued. In this research, an automatic method is presented. Firstly, a proposed locally adaptive thresholding method is used to segment chromosome clusters. Then, the clusters is divided into two main categories including, single chromosomes and multi-chromosome clusters based on geometric shape of clusters. In the next step, each extracted cluster is investigated to find the dark paths in order to detect touching chromosomes. Then, overlapping chromosomes are separated in clusters based on their geometric shapes. Finally, a criterion function is used to measure the similarity between the outputs of the proposed algorithm and the single chromosomes in order to recognize separated parts. The proposed algorithm is applied on 47 G-band images. The results shows that single chromosomes and clusters are recognized by the precision of 98.5% and 86.4%, respectively and separation of touching and overlapping clusters are done by precision of 70% and 67%, respectively.

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