A comprehensive review on the utility of capsule endoscopy in coeliac disease: From computational analysis to the bedside
Small bowel capsule endoscopy (SBCE) can identify macroscopic changes of coeliac disease and assess the extent of disease in the small bowel beyond the duodenum. SBCE has a good sensitivity for the detection of coeliac disease in comparison to histology owing to several ideal features such as a high...
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Published in | Computers in biology and medicine Vol. 102; pp. 300 - 314 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
United States
Elsevier Ltd
01.11.2018
Elsevier Limited |
Subjects | |
Online Access | Get full text |
ISSN | 0010-4825 1879-0534 1879-0534 |
DOI | 10.1016/j.compbiomed.2018.06.025 |
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Summary: | Small bowel capsule endoscopy (SBCE) can identify macroscopic changes of coeliac disease and assess the extent of disease in the small bowel beyond the duodenum.
SBCE has a good sensitivity for the detection of coeliac disease in comparison to histology owing to several ideal features such as a high magnification. It also plays a useful role in detecting complications in patients with refractory coeliac disease. Several studies have been carried out on transforming images obtained from small bowel capsule endoscopy to enable the automated detection of features related to coeliac disease.
This review discusses the current roles played by small bowel capsule endoscopy in coeliac disease. It identifies future potential roles of this technique and describes in great detail the role of computational analysis in the detection of coeliac disease and how it can be adapted to current available technology.
•Features of coeliac disease on small bowel capsule endoscopy are currently picked up by human readers which is time consuming and subject to bias.•Macroscopic features of coeliac disease include fissuring of mucosa, mosaic pattern, nodularity and scalloping of folds.•Small bowel capsule endoscopy is indicated in equivocal cases, where complications are suspected and in refractory coeliac disease.•Automated detection of coeliac disease involves texture analysis of three dimensional images derived from small bowel capsule endoscopy.•GoogLeNet and an automated polling system for the detection of coeliac disease have been tested on a small number of capsule endoscopy videos. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 ObjectType-Review-3 content type line 23 |
ISSN: | 0010-4825 1879-0534 1879-0534 |
DOI: | 10.1016/j.compbiomed.2018.06.025 |