NDLI: Discriminative sparse representations for cervigram image segmentation

Content Provider	IEEE Xplore Digital Library
Author	Shaoting Zhang Junzhou Huang Metaxas, D. Wei Wang Xiaolei Huang
Copyright Year	2010
Description	Author affiliation: CBIM, Rutgers University, Computer Science Department, USA (Shaoting Zhang; Junzhou Huang; Metaxas, D.) \|\| Lehigh University, Computer Science Department, USA (Wei Wang; Xiaolei Huang)
Abstract	This paper presents an algorithm using discriminative sparse representations to segment tissues in optical images of the uterine cervix. Because of the large variations in the image appearance caused by the changing of illumination and specular reflection, the different classes of color and texture features in optical images are often overlapped with each other. Using sparse representations they can be transformed to higher dimension with sparse constraints and become more linearly separated. Different from the previous reconstructive sparse representation, the discriminative method considers positive and negative samples simultaneously, which means that these generated dictionaries can be discriminative and perform better for their own classes but worse for the others. New data can be reconstructed from its sparse representations and positive and/or negative dictionaries. Classification can be achieved based on comparing the reconstructive errors. In the experiments we used our method to automatically segment the biomarker AcetoWhite (AW) regions in an archive of the uterine cervix. Compared with the other general methods including SVM, nearest neighbor and reconstructive sparse representations, our approach showed higher sensitivity and specificity.
Starting Page	133
Ending Page	136
File Size	568208
Page Count	4
File Format	PDF
ISBN	9781424441259
ISSN	19457928
DOI	10.1109/ISBI.2010.5490397
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-04-14
Publisher Place	Netherlands
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image segmentation Image reconstruction Biomedical optical imaging Optical sensors Dictionaries Lighting Optical reflection Biomarkers Support vector machines Support vector machine classification classification segmentation cervix image biomarker AcetoWhite discriminative sparse representation reconstructive errors
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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