Azzopardi, Carl, Hicks, Yulia Alexandrovna ![]() |
Abstract
Capsule Endoscopy is a technique designed to wirelessly image the small intestine within the gastrointestinal (GI) tract. Its main drawback is the vast amount of images it generates per patient, necessitating long screening sessions by the clinician. Previous studies have proposed to partially facilitate this process by automatically segmenting the GI tract into its constituent organs, thus identifying the region of interest. In this work, we propose to exploit the anatomical structure of the GI tract when carrying out dimensionality reduction on visual feature vectors that describe the capsule images. To this end, we suggest a novel adaptation of a technique called Locality Preserving Projections, and results show that this achieves an improved performance in organ classification and segmentation, at no additional computational or memory cost.
Item Type: | Conference or Workshop Item (Paper) |
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Date Type: | Publication |
Status: | Published |
Schools: | Engineering |
Subjects: | R Medicine > R Medicine (General) T Technology > TA Engineering (General). Civil engineering (General) |
Publisher: | IEEE |
ISSN: | 1557-170X |
Related URLs: | |
Last Modified: | 25 Oct 2022 09:40 |
URI: | https://orca.cardiff.ac.uk/id/eprint/59569 |
Citation Data
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