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IsletSwipe, a mobile platform for expert opinion exchange on islet graft images
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SYSNO ASEP 0571406 Document Type J - Journal Article R&D Document Type Journal Article Subsidiary J Článek ve WOS Title IsletSwipe, a mobile platform for expert opinion exchange on islet graft images Author(s) Habart, D. (CZ)
Koza, A. (CZ)
Leontovyč, I. (CZ)
Kosinová, L. (CZ)
Berková, Z. (CZ)
Kříž, J. (CZ)
Zacharovová, K. (CZ)
Brinkhof, B. (NL)
Cornelissen, D. J. (NL)
Magrane, N. (GB)
Bittenglová, K. (CZ)
Čapek, Martin (FGU-C) RID, ORCID
Valečka, J. (CZ)
Habartová, Alena (UOCHB-X) RID
Saudek, F. (CZ)Article number 2189873 Source Title Islets. - : Landes Bioscience - ISSN 1938-2014
Roč. 15, č. 1 (2023)Number of pages 15 s. Language eng - English Country US - United States Keywords consensus building ; deep learning ; expert opinion exchange ; ground truth ; human islets ; image annotation ; islet counting ; mobile application ; islet graft quality control ; islet isolation ; islet transplantation ; user experience OECD category Transplantation R&D Projects NU22-01-00141 GA MZd - Ministry of Health (MZ) LX22NPO5104 GA MŠMT - Ministry of Education, Youth and Sports (MEYS) LM2018129 GA MŠMT - Ministry of Education, Youth and Sports (MEYS) EF18_046/0016045 GA MŠMT - Ministry of Education, Youth and Sports (MEYS) Method of publishing Open access Institutional support FGU-C - RVO:67985823 ; UOCHB-X - RVO:61388963 UT WOS 000959035100001 EID SCOPUS 85151112347 DOI 10.1080/19382014.2023.2189873 Annotation We previously developed a deep learning-based web service (IsletNet) for an automated counting of isolated pancreatic islets. The neural network training is limited by the absent consensus on the ground truth annotations. Here, we present a platform (IsletSwipe) for an exchange of graphical opinions among experts to facilitate the consensus formation. The platform consists of a web interface and a mobile application. In a small pilot study, we demonstrate the functionalities and the use case scenarios of the platform. Nine experts from three centers validated the drawing tools, tested precision and consistency of the expert contour drawing, and evaluated user experience. Eight experts from two centers proceeded to evaluate additional images to demonstrate the following two use case scenarios. The Validation scenario involves an automated selection of images and islets for the expert scrutiny. It is scalable (more experts, images, and islets may readily be added) and can be applied to independent validation of islet contours from various sources. The Inquiry scenario serves the ground truth generating expert in seeking assistance from peers to achieve consensus on challenging cases during the preparation for IsletNet training. This scenario is limited to a small number of manually selected images and islets. The experts gained an opportunity to influence IsletNet training and to compare other experts’ opinions with their own. The ground truth-generating expert obtained feedback for future IsletNet training. IsletSwipe is a suitable tool for the consensus finding. Experts from additional centers are welcome to participate. Workplace Institute of Physiology Contact Lucie Trajhanová, lucie.trajhanova@fgu.cas.cz, Tel.: 241 062 400 Year of Publishing 2024 Electronic address https://doi.org/10.1080/19382014.2023.2189873
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