Automated classification of celiac disease during upper endoscopy: Status quo and quo vadis

Gadermayr M, Wimmer G, Kogler H, Vecsei A, Merhof D, Uhl A (2018)

Publication Type: Journal article

Publication year: 2018

Journal

Computers in Biology and Medicine Elsevier

Book Volume: 102

Pages Range: 221-226

DOI: 10.1016/j.compbiomed.2018.04.020

Abstract

A large amount of digital image material is routinely captured during esophagogastroduodenoscopies but, for the most part, is not used for confirming the diagnosis process of celiac disease which is primarily based on histological examination of biopsies. Recently, considerable effort has been undertaken to make use of image material by developing semi- or fully-automated systems to improve the diagnostic workup. Recently, focus was especially laid on developing state-of-the-art deep learning architectures, exploiting the endoscopist's expert knowledge and on making systems fully automated and thereby completely observer independent. In this work, we summarize recent trends in the field of computer-aided celiac disease diagnosis based on upper endoscopy and discuss about recent progress, remaining challenges, limitations currently prohibiting a deployment in clinical practice and future efforts to tackle them.

Involved external institutions

St. Anna Kinderkrebsforschung AT Austria (AT) Rheinisch-Westfälische Technische Hochschule (RWTH) Aachen DE Germany (DE) Universität Salzburg (Paris Lodron Universität Salzburg) AT Austria (AT)

How to cite

APA:

Gadermayr, M., Wimmer, G., Kogler, H., Vecsei, A., Merhof, D., & Uhl, A. (2018). Automated classification of celiac disease during upper endoscopy: Status quo and quo vadis. Computers in Biology and Medicine, 102, 221-226. https://doi.org/10.1016/j.compbiomed.2018.04.020

MLA:

Gadermayr, M., et al. "Automated classification of celiac disease during upper endoscopy: Status quo and quo vadis." Computers in Biology and Medicine 102 (2018): 221-226.

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