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DINOSARC: Color Features Based on Selective Aggregation of Chromatic Image Components for Wireless Capsule Endoscopy
Joint Authors
Iakovidis, D. K.
Koulaouzidis, Anastasios
Vasilakakis, Michael D.
Spyrou, Evaggelos
Source
Computational and Mathematical Methods in Medicine
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-09-03
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
Wireless Capsule Endoscopy (WCE) is a noninvasive diagnostic technique enabling the inspection of the whole gastrointestinal (GI) tract by capturing and wirelessly transmitting thousands of color images.
Proprietary software “stitches” the images into videos for examination by accredited readers.
However, the videos produced are of large length and consequently the reading task becomes harder and more prone to human errors.
Automating the WCE reading process could contribute in both the reduction of the examination time and the improvement of its diagnostic accuracy.
In this paper, we present a novel feature extraction methodology for automated WCE image analysis.
It aims at discriminating various kinds of abnormalities from the normal contents of WCE images, in a machine learning-based classification framework.
The extraction of the proposed features involves an unsupervised color-based saliency detection scheme which, unlike current approaches, combines both point and region-level saliency information and the estimation of local and global image color descriptors.
The salient point detection process involves estimation of DIstaNces On Selective Aggregation of chRomatic image Components (DINOSARC).
The descriptors are extracted from superpixels by coevaluating both point and region-level information.
The main conclusions of the experiments performed on a publicly available dataset of WCE images are (a) the proposed salient point detection scheme results in significantly less and more relevant salient points; (b) the proposed descriptors are more discriminative than relevant state-of-the-art descriptors, promising a wider adoption of the proposed approach for computer-aided diagnosis in WCE.
American Psychological Association (APA)
Vasilakakis, Michael D.& Iakovidis, D. K.& Spyrou, Evaggelos& Koulaouzidis, Anastasios. 2018. DINOSARC: Color Features Based on Selective Aggregation of Chromatic Image Components for Wireless Capsule Endoscopy. Computational and Mathematical Methods in Medicine،Vol. 2018, no. 2018, pp.1-11.
https://search.emarefa.net/detail/BIM-1131817
Modern Language Association (MLA)
Vasilakakis, Michael D.…[et al.]. DINOSARC: Color Features Based on Selective Aggregation of Chromatic Image Components for Wireless Capsule Endoscopy. Computational and Mathematical Methods in Medicine No. 2018 (2018), pp.1-11.
https://search.emarefa.net/detail/BIM-1131817
American Medical Association (AMA)
Vasilakakis, Michael D.& Iakovidis, D. K.& Spyrou, Evaggelos& Koulaouzidis, Anastasios. DINOSARC: Color Features Based on Selective Aggregation of Chromatic Image Components for Wireless Capsule Endoscopy. Computational and Mathematical Methods in Medicine. 2018. Vol. 2018, no. 2018, pp.1-11.
https://search.emarefa.net/detail/BIM-1131817
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1131817