NDLI: Classification of multicolor fluorescence in-situ hybridization (M-FISH) image using structure based sparse representation model

Content Provider	IEEE Xplore Digital Library
Author	Jingyao Li Dongdong Lin Hongbao Cao Yu-Ping Wang
Copyright Year	2012
Description	Author affiliation: Department of Biomedicai Engineering, Tulane University, New Orleans, LA, USA (Jingyao Li; Dongdong Lin; Hongbao Cao; Yu-Ping Wang)
Abstract	We developed a structure based sparse representation model for classifying chromosomes in M-FISH images. The sparse representation based classification model used in our previous work only considered one pixel without incorporating any structural information. The new proposed model extends the previous one to multiple pixels case, where each target pixel together with its neighboring pixels will be used simultaneously for classification. We also extend Orthogonal Matching Pursuit (OMP) algorithm to the multiple pixels case, named simultaneous OMP algorithm (SOMP), to solve the structure based sparse representation model. The classification results show that our new model outperforms the previous sparse representation model with the p-value less than le-6. We also discussed the effects of several parameters (neighborhood size, sparsity level, and training sample size) on the accuracy of the classification. Our proposed method can be affected by the sparsity level and the neighborhood size but is insensitive to the training sample size. Therefore, the comparison indicates that the structure based sparse representation model can significantly improve the accuracy of the chromosome classification, leading to improved diagnosis of genetic diseases and cancers.
Starting Page	1
Ending Page	6
File Size	8078515
Page Count	6
File Format	PDF
ISBN	9781467325592
e-ISBN	9781467325608
e-ISBN	9781467325585
DOI	10.1109/BIBM.2012.6392672
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-10-04
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Training Analytical models Accuracy structure based sparse model Matching pursuit algorithms M-FISH Classification algorithms Sparse matrices Biological cells chromosome classification
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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