Endoscopy, video capsule endoscopy, and biopsy for automated celiac disease detection: A review

• Autorzy: Jahmunah V. , En Wei Koh Joel , Sudarshan Vidya K. , Raghavendra U. , Gudigar Anjan , Lih Oh Shu , Wen Loh Hui , Faust Oliver , Datta Barua Prabal , Ciaccio Edward J. , Rajendra Acharya U.

Identyfikatory

DOI

10.1016/j.bbe.2022.12.002

• Języki publikacji: EN

Abstrakty

EN

Celiac Disease (CD) is a common ailment that affects approximately 1% of the world population. Automated CD detection can help experts during the diagnosis of this condition at an early stage and bring significant benefits to both patients and healthcare providers. For this purpose, scientists have created automatic and semi-automatic CD diagnostic support systems. In this study, we performed information extraction methods that were found useful for efforts to differentiate CD versus non-CD. To focus the review process, only methods for endoscopy, video capsule endoscopy (VCE) and biopsy image analyses were considered. As described herein, we have learned that statistical and non-linear methods are most important for information extraction. These information extraction tools might benefit clinical workflows by reducing intra- and inter-observer variability. However, bias, introduced by resolving design choices during the creation of diagnostic support systems, may limit the general validity of the performance results, impacting the transferability of study outcomes. Therefore, having am overview of information extraction tools. Together with their general and specific limitations, might be assistive in improving the information extraction process. We hope our review results will provide a foundation for the design of next-generation statistical and nonlinear methods that can be used in CD detection systems. We have also compared various review articles and discussed recommendations to improve CD diagnosis. From this review, it is evident that CD diagnosis is slowly moving away from conventional techniques towards advanced deep learning techniques.

Słowa kluczowe

EN

celiac disease; video capsule endoscopy; nonlinear feature; statistical analysis

PL

celiakia; endoskopia kapsułkowa; funkcja nieliniowa; analiza statystyczna

• Wydawca: Nałęcz Institute of Biocybernetics and Biomedical Engineering of the Polish Academy of Sciences ; Elsevier
• Czasopismo: Biocybernetics and Biomedical Engineering
• Rocznik: 2023
• Tom: Vol. 43, no. 1
• Strony: 82--108
• Opis fizyczny: Bibliogr. 110 poz., rys., tab., wykr.

Twórcy

autor

Jahmunah V.

• School of Engineering, Ngee Ann Polytechnic, Singapore

autor

En Wei Koh Joel

• School of Engineering, Ngee Ann Polytechnic, Singapore

autor

Sudarshan Vidya K.

• School of Science and Technology, Singapore University of Social Sciences, Singapore

autor

Raghavendra U.

• Department of Instrumentation and Control Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, India

autor

Gudigar Anjan

• Department of Instrumentation and Control Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, India

autor

Lih Oh Shu

• School of Engineering, Ngee Ann Polytechnic, Singapore

autor

Wen Loh Hui

• School of Science and Technology, Singapore University of Social Sciences, Singapore

autor

Faust Oliver

• Department of Computer Science, Anglia Ruskin University, Cambridge, United Kingdom

autor

Datta Barua Prabal

• School of Management and Enterprise University of Southern Queensland Springfield, Australia
• Faculty of Engineering and Information Technology, University of Technology Sydney, Australia
• Cogninet Brain Team, Cogninet Australia, Sydney, Australia

autor

Ciaccio Edward J.

• Department of Medicine – Celiac Disease Center, Columbia University Irving Medical Center, USA

autor

Rajendra Acharya U.

• School of Engineering, Ngee Ann Polytechnic, Singapore
• School of Science and Technology, Singapore University of Social Sciences, Singapore
• Department of Bioinformatics and Medical Engineering, Asia University, Taiwan
• International Research Organization for Advanced Science and Technology (IROAST), Kumamoto University, Kumamoto, Japan

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Uwagi

PL

Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023)