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IsletSwipe, a mobile platform for expert opinion exchange on islet graft images

D. Habart, A. Koza, I. Leontovyc, L. Kosinova, Z. Berkova, J. Kriz, K. Zacharovova, B. Brinkhof, DJ. Cornelissen, N. Magrane, K. Bittenglova, M. Capek, J. Valecka, A. Habartova, F. Saudek

. 2023 ; 15 (1) : 2189873. [pub] 2023Dec31

Language English Country United States

Document type Journal Article

Persistent link   https://www.medvik.cz/link/bmc23003575

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.

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$a We previously developed a deep learning-based web service (IsletNet) for an automated counting of isolated pancreatic islets. The neural network training is limited by the absent consensus on the ground truth annotations. Here, we present a platform (IsletSwipe) for an exchange of graphical opinions among experts to facilitate the consensus formation. The platform consists of a web interface and a mobile application. In a small pilot study, we demonstrate the functionalities and the use case scenarios of the platform. Nine experts from three centers validated the drawing tools, tested precision and consistency of the expert contour drawing, and evaluated user experience. Eight experts from two centers proceeded to evaluate additional images to demonstrate the following two use case scenarios. The Validation scenario involves an automated selection of images and islets for the expert scrutiny. It is scalable (more experts, images, and islets may readily be added) and can be applied to independent validation of islet contours from various sources. The Inquiry scenario serves the ground truth generating expert in seeking assistance from peers to achieve consensus on challenging cases during the preparation for IsletNet training. This scenario is limited to a small number of manually selected images and islets. The experts gained an opportunity to influence IsletNet training and to compare other experts' opinions with their own. The ground truth-generating expert obtained feedback for future IsletNet training. IsletSwipe is a suitable tool for the consensus finding. Experts from additional centers are welcome to participate.
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$a Koza, Adam $u Dino School & Novy PORG, Prague, Czech Republic
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$a Leontovyc, Ivan $u Laboratory of Pancreatic Islets, Center of Experimental Medicine, Institute for Clinical and Experimental Medicine (IKEM), Prague, Czech Republic
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$a Kosinova, Lucie $u Laboratory of Pancreatic Islets, Center of Experimental Medicine, Institute for Clinical and Experimental Medicine (IKEM), Prague, Czech Republic
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$a Berkova, Zuzana $u Laboratory of Pancreatic Islets, Center of Experimental Medicine, Institute for Clinical and Experimental Medicine (IKEM), Prague, Czech Republic
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$a Kriz, Jan $u Diabetes Center, Institute for Clinical and Experimental Medicine, Prague, Czech Republic
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$a Zacharovova, Klara $u Laboratory of Pancreatic Islets, Center of Experimental Medicine, Institute for Clinical and Experimental Medicine (IKEM), Prague, Czech Republic
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$a Magrane, Nicholas $u Nuffield department of surgical sciences, Oxford Consortium for Islet transplantation, Oxford, UK
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$a Bittenglova, Katerina $u Diabetes Center, Institute for Clinical and Experimental Medicine, Prague, Czech Republic
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$a Capek, Martin $u Light Microscopy Laboratory, Institute of Molecular Genetics of the Czech Academy of Sciences, Prague, Czech Republic $u Laboratory of Biomathematics, Institute of Physiology of the Czech Academy of Sciences, Prague, Czech Republic
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$a Valecka, Jan $u Laboratory of Biomathematics, Institute of Physiology of the Czech Academy of Sciences, Prague, Czech Republic
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$a Habartova, Alena $u Redox Photochemistry Lab, Institute of Organic Chemistry and Biochemistry of the Czech Academy of Sciences, Prague, Czech Republic
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