Understanding Graph Convolutional Networks to detect Brain Lesions from Stroke

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dc.contributor.authorIporre-Rivas, Arielen_US
dc.contributor.authorScheuermann, Geriken_US
dc.contributor.authorGillmann, Christinaen_US
dc.contributor.editorRenata G. Raidouen_US
dc.contributor.editorBjörn Sommeren_US
dc.contributor.editorTorsten W. Kuhlenen_US
dc.contributor.editorMichael Kroneen_US
dc.contributor.editorThomas Schultzen_US
dc.contributor.editorHsiang-Yun Wuen_US
dc.date.accessioned2022-09-19T11:46:35Z
dc.date.available2022-09-19T11:46:35Z
dc.date.issued2022
dc.description.abstractBrain lesions derived from stroke episodes can result in disabilities for a patient. Therefore, the segmentation of brain lesions is an important task in neurology. Recently this task has been mainly tackled by machine learning approaches that demonstrated to be very successful. One of these approaches is Graph Convolutional Networks (GCN), where the input image is interpreted as a graph structure. As usual for neural networks, the interpretability is hard due to their black-box nature. We provide an interactive visualization of the activation inherent in the GCN, which is map from the original dataset. We visualize the activation values of the underlying graph network on top of the input image. We show the usability of our approach by applying it to a GCN that was trained on a real-world dataset.en_US
dc.description.sectionheadersVisual Analytics, Artificial Intelligence
dc.description.seriesinformationEurographics Workshop on Visual Computing for Biology and Medicine
dc.identifier.doi10.2312/vcbm.20221195
dc.identifier.isbn978-3-03868-177-9
dc.identifier.issn2070-5786
dc.identifier.pages123-127
dc.identifier.pages5 pages
dc.identifier.urihttps://doi.org/10.2312/vcbm.20221195
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/vcbm20221195
dc.publisherThe Eurographics Associationen_US
dc.rightsAttribution 4.0 International License
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.titleUnderstanding Graph Convolutional Networks to detect Brain Lesions from Strokeen_US
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VCBM 2022: Eurographics Workshop on Visual Computing for Biology and Medicine