NDLI: Curvelet-based classification of prostate cancer histological images of critical Gleason scores

Content Provider	IEEE Xplore Digital Library
Author	Wen-Chyi Lin Ching-Chung Li Christudass, C.S. Epstein, J.I. Veltri, R.W.
Copyright Year	2015
Description	Author affiliation: Depts. of Urology & Oncology, Johns Hopkins Univ., Baltimore, MD, USA (Christudass, C.S.; Epstein, J.I.; Veltri, R.W.) \|\| Dept. of Electr. & Comput. Eng., Univ. of Pittsburgh, Pittsburgh, PA, USA (Wen-Chyi Lin; Ching-Chung Li)
Abstract	This paper is aimed at the development of an approach of applying the curvelet transform to images of prostatectomy pathological specimens of critical Gleason grades for computer-aided classification. A set of Tissue MicroArray (TMA) images from the Johns Hopkins University have been used as the data base. We utilize a moving window to sample multiple patches of a given image leading to a majority decision by the patches for image class assignment. The curvelet-based feature extraction may capture both textural and, implicitly, structural information in an image patch. A tree-structured classifier consisting of three Gaussian-kernel support vector machines each with an embedded voting mechanism has been successfully trained and tested yielding high accuracy to classify tissue images of four critical Gleason scores (GS) 3+3, 3+4, 4+3 and 4+4. The experimental result has demonstrated an enhanced performance as compared to other reported works.
Starting Page	1020
Ending Page	1023
File Size	639065
Page Count	4
File Format	PDF
ISBN	9781479923748
DOI	10.1109/ISBI.2015.7164044
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-04-16
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Prostate cancer Transforms Support vector machines Training Feature extraction Biological tissues Accuracy Gleason scores Curvelets tissue texture classification prostate cancer Gleason grading
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
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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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