M-FISH Chromosome Images Classification by Watershed Based Segmentation Approach

Karyotyping is a technique used to display and study the human chromosomes for detecting abnormalities, genetic disorders or defects. M-FISH (Multiplex Fluorescent In-Situ Hybridization) provides color karyotyping. In this paper, naïve Bayes classification of M-FISH chromosome images based on watershed based chromosome segmentation is presented. It is observed that the classification of the watershed regions by using the naive Bayes classifier works better than pixel by pixel classification. By adding the feature, standard deviation along with mean of each region, improved classification accuracy was observed. The approach was tested on a database and found to provide an accuracy of 73%. KeywordsM-FISH, chromosome, segmentation, karyotyping, watershed transform, Bayes classifier.

[1]  Dimitrios I. Fotiadis,et al.  Semi unsupervised M-FISH chromosome image classification , 2010, Proceedings of the 10th IEEE International Conference on Information Technology and Applications in Biomedicine.

[2]  Alan C. Bovik,et al.  Pixel-by-pixel classification of MFISH images , 2002, Proceedings of the Second Joint 24th Annual Conference and the Annual Fall Meeting of the Biomedical Engineering Society] [Engineering in Medicine and Biology.

[3]  Kevin Barraclough,et al.  I and i , 2001, BMJ : British Medical Journal.

[4]  Luc Vincent,et al.  Watersheds in Digital Spaces: An Efficient Algorithm Based on Immersion Simulations , 1991, IEEE Trans. Pattern Anal. Mach. Intell..

[5]  Rafael C. González,et al.  Local Determination of a Moving Contrast Edge , 1985, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[6]  D. Ward,et al.  Karyotyping human chromosomes by combinatorial multi-fluor FISH , 1996, Nature Genetics.

[7]  Amala Chaudhuri,et al.  The chromosome number in man , 1963, Indian journal of pediatrics.

[8]  Jake K. Aggarwal,et al.  Supervised parametric and non-parametric classification of chromosome images , 2005, Pattern Recognit..

[9]  D. Ledbetter,et al.  Multicolor Spectral Karyotyping of Human Chromosomes , 1996, Science.

[10]  K. Castleman,et al.  Joint segmentation and classification of M-FISH chromosome images , 2004, The 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[11]  Dimitrios I. Fotiadis,et al.  Enhancement of Multichannel Chromosome Classification Using a Region-Based Classifier and Vector Median Filtering , 2009, IEEE Transactions on Information Technology in Biomedicine.

[12]  Alan C. Bovik,et al.  Maximum-likelihood techniques for joint segmentation-classification of multispectral chromosome images , 2005, IEEE Transactions on Medical Imaging.

[13]  Dimitrios I. Fotiadis,et al.  A Multichannel Watershed-Based Segmentation Method for Multispectral Chromosome Classification , 2008, IEEE Transactions on Medical Imaging.

[14]  N. Otsu.  A threshold selection method from gray level histograms , 1979 .

[15]  D.I. Fotiadis,et al.  A Watershed Based Segmentation Method for Multispectral Chromosome Images Classification , 2006, 2006 International Conference of the IEEE Engineering in Medicine and Biology Society.

[16]  Alan C. Bovik,et al.  Segmentation and Fuzzy-Logic Classification of M-FISH Chromosome Images , 2006, 2006 International Conference on Image Processing.

[17]  Alan C. Bovik,et al.  Color Compensation of Multicolor FISH Images , 2009, IEEE Transactions on Medical Imaging.

[18]  Shigeo Abe DrEng.  Pattern Classification , 2001, Springer London.

[19]  H. Choi,et al.  Automatic segmentation and classification of multiplex -fluorescence in -situ hybridization chromosome images , 2006 .