International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
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Volume 70 - Issue 25 |
Published: May 2013 |
Authors: Lijiya A, Sreejithlal G S, Govindan V K |
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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.