NDLI: Computer-aided detection of colitis on computed tomography using a visual codebook

Content Provider	IEEE Xplore Digital Library
Author	Zhuoshi Wei Weidong Zhang Jianfei Liu Shijun Wang Jianhua Yao Summers, R.M.
Copyright Year	2013
Description	Author affiliation: Dept. of Radiol. & Imaging Sci., Nat. Inst. of Health Clinical Center, Bethesda, MD, USA (Zhuoshi Wei; Weidong Zhang; Jianfei Liu; Shijun Wang; Jianhua Yao; Summers, R.M.)
Abstract	Colitis is inflammation of the colon that is frequently associated with infection and immune compromise. In this paper, we propose an automatic method for colitis detection in abdominal CT scans. We first used a visual codebook constructed by clustering feature vectors from a set of training image patches to detect the suspicious colitis regions. The initial detections included false detection points located in various organs including muscle, kidney and liver. We reduced the false positives by applying masks of these regions obtained from whole-organ segmentation. We tested our method on a CT dataset with 20 cases of colitis and 15 non-colitis cases. Average detected lesion volume for positive cases is 205ml; for negative cases is 97ml. Sixteen out of the 22 positive cases were correctly identified, yielding a sensitivity of 72.7%; 4 out of 15 negative cases were incorrectly identified, yielding a specificity of 73.3%.
Sponsorship	IEEE
Starting Page	141
Ending Page	144
File Size	866691
Page Count	4
File Format	PDF
ISBN	9781467364560
ISSN	19457928
e-ISBN	9781467364553
DOI	10.1109/ISBI.2013.6556432
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-04-07
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Computed tomography Training Visualization Kidney Muscles Colon Feature extraction visual codebook CT colon colitis
Content Type	Text
Resource Type	Article

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