%0 Journal Article %1 noauthororeditor %A S, Sreejini K %A A, Lijiya %A Govindan, V K %D 2012 %J International Journal of Computer Science, Engineering and Information Technology (IJCSEIT) %K Bayes Chromosome Karyotyping M-FISH Watershed classifier image segmentation transform %N 2 %P 105-117 %R 10.5121/ijcseit.2012.2210 %T M-FISH KARYOTYPING - A NEW APPROACH BASED ON WATERSHED TRANSFORM %U http://airccse.org/journal/ijcseit/papers/2212ijcseit10.pdf %V 2 %X 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 %.

@article{noauthororeditor, 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 %. }, added-at = {2018-07-07T08:53:45.000+0200}, author = {S, Sreejini K and A, Lijiya and Govindan, V K}, biburl = {https://www.bibsonomy.org/bibtex/28ec325477502322ec646c46a9dca186e/ijcseit}, doi = {10.5121/ijcseit.2012.2210}, interhash = {ef04b0d2f481a351a7c0564e3da8dbd0}, intrahash = {8ec325477502322ec646c46a9dca186e}, issn = {2231-3117 [Online] ; 2231-3605 [Print]}, journal = {International Journal of Computer Science, Engineering and Information Technology (IJCSEIT)}, keywords = {Bayes Chromosome Karyotyping M-FISH Watershed classifier image segmentation transform}, language = {English}, month = apr, number = 2, pages = {105-117}, timestamp = {2018-07-07T08:53:45.000+0200}, title = {M-FISH KARYOTYPING - A NEW APPROACH BASED ON WATERSHED TRANSFORM}, url = {http://airccse.org/journal/ijcseit/papers/2212ijcseit10.pdf}, volume = 2, year = 2012 }