|
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
|
| Volume 70 - Issue 25 |
| Published: May 2013 |
| Authors: Lijiya A, Sreejithlal G S, Govindan V K |
10.5120/12227-8519
|
Lijiya A, Sreejithlal G S, Govindan V K . M-FISH Image Segmentation and Classification using Fuzzy Logic. International Journal of Computer Applications. 70, 25 (May 2013), 46-51. DOI=10.5120/12227-8519
@article{ 10.5120/12227-8519,
author = { Lijiya A,Sreejithlal G S,Govindan V K },
title = { M-FISH Image Segmentation and Classification using Fuzzy Logic },
journal = { International Journal of Computer Applications },
year = { 2013 },
volume = { 70 },
number = { 25 },
pages = { 46-51 },
doi = { 10.5120/12227-8519 },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2013
%A Lijiya A
%A Sreejithlal G S
%A Govindan V K
%T M-FISH Image Segmentation and Classification using Fuzzy Logic%T
%J International Journal of Computer Applications
%V 70
%N 25
%P 46-51
%R 10.5120/12227-8519
%I Foundation of Computer Science (FCS), NY, USA
Karyotyping has an important role in identifying genetic disorders due to structural changes in chromosomes. Multiplex fluorescence in-situ hybridization (M-FISH) technique provides more precise karyotyping. The new classification method, proposed in this paper, automates karyotyping, based on Fuzzy c-means (FCM) algorithm combined with a labeling chart. Classification results show that the proposed method improves accuracy and running time. It is also observed that the accuracy of classification can further be improved, using a new Reclassification algorithm which reduces the chance of wrongly classified chromosome pixels.