LASSNet: A Four Steps Deep Neural Network for Left Atrial Segmentation and Scar Quantification.

Autor: Lefebvre AL; Faculté polytechnique de Mons, UMONS, Mons, Belgium.; Alliance for Cardiovascular Diagnostic and Treatment Innovation (ADVANCE), Johns Hopkins University, Baltimore, MD, USA., Yamamoto CAP; Alliance for Cardiovascular Diagnostic and Treatment Innovation (ADVANCE), Johns Hopkins University, Baltimore, MD, USA.; Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, USA., Shade JK; Alliance for Cardiovascular Diagnostic and Treatment Innovation (ADVANCE), Johns Hopkins University, Baltimore, MD, USA., Bradley RP; Alliance for Cardiovascular Diagnostic and Treatment Innovation (ADVANCE), Johns Hopkins University, Baltimore, MD, USA., Yu RA; Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, USA., Ali RL; Alliance for Cardiovascular Diagnostic and Treatment Innovation (ADVANCE), Johns Hopkins University, Baltimore, MD, USA.; Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, USA., Popescu DM; Alliance for Cardiovascular Diagnostic and Treatment Innovation (ADVANCE), Johns Hopkins University, Baltimore, MD, USA., Prakosa A; Alliance for Cardiovascular Diagnostic and Treatment Innovation (ADVANCE), Johns Hopkins University, Baltimore, MD, USA., Kholmovski EG; Alliance for Cardiovascular Diagnostic and Treatment Innovation (ADVANCE), Johns Hopkins University, Baltimore, MD, USA.; Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, USA., Trayanova NA; Alliance for Cardiovascular Diagnostic and Treatment Innovation (ADVANCE), Johns Hopkins University, Baltimore, MD, USA.; Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Jazyk: angličtina
Zdroj: Left atrial and scar quantification and segmentation : first challenge, LAScarQS 2022 held in conjunction with MICCAI 2022, Singapore, September 18, 2022, proceedings [Left Atr Scar Quantif Segm (2022)] 2023; Vol. 13586, pp. 1-15. Date of Electronic Publication: 2023 May 05.
DOI: 10.1007/978-3-031-31778-1_1
Abstrakt: 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.
Databáze: MEDLINE
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