Left atrial and scar quantification and segmentation : first challenge, LAScarQS 2022 held in conjunction with MICCAI 2022, Singapore, September 18, 2022, proceedings最新文献
Pub Date : 2023-01-01DOI: 10.1007/978-3-031-31778-1_1
Arthur L Lefebvre, Carolyna A P Yamamoto, Julie K Shade, Ryan P Bradley, Rebecca A Yu, Rheeda L Ali, Dan M Popescu, Adityo Prakosa, Eugene G Kholmovski, Natalia A Trayanova
Accurate quantification of left atrium (LA) scar in patients with atrial fibrillation is essential to guide successful ablation strategies. Prior to LA scar quantification, a proper LA cavity segmentation is required to ensure exact location of scar. Both tasks can be extremely time-consuming and are subject to inter-observer disagreements when done manually. We developed and validated a deep neural network to automatically segment the LA cavity and the LA scar. The global architecture uses a multi-network sequential approach in two stages which segment the LA cavity and the LA Scar. Each stage has two steps: a region of interest Neural Network and a refined segmentation network. We analysed the performances of our network according to different parameters and applied data triaging. 200+ late gadolinium enhancement magnetic resonance images were provided by the LAScarQS 2022 Challenge. Finally, we compared our performances for scar quantification to the literature and demonstrated improved performances.
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Pub Date : 1900-01-01DOI: 10.1007/978-3-031-31778-1
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Left atrial and scar quantification and segmentation : first challenge, LAScarQS 2022 held in conjunction with MICCAI 2022, Singapore, September 18, 2022, proceedings
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