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245 1 0 _aSegmentation of the Aorta. Towards the Automatic Segmentation, Modeling, and Meshing of the Aortic Vessel Tree from Multicenter Acquisition
_h[electronic resource] :
_bFirst Challenge, SEG.A. 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8, 2023, Proceedings /
_cedited by Antonio Pepe, Gian Marco Melito, Jan Egger.
250 _a1st ed. 2024.
264 1 _aCham :
_bSpringer Nature Switzerland :
_bImprint: Springer,
_c2024.
300 _aXII, 142 p. 74 illus., 67 illus. in color.
_bonline resource.
336 _atext
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337 _acomputer
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338 _aonline resource
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490 1 _aLecture Notes in Computer Science,
_x1611-3349 ;
_v14539
505 0 _aM3F: Multi-Field-of-View Feature Fusion Network for Aortic Vessel Tree Segmentation in CT Angiography -- Aorta Segmentation from 3D CT in MICCAI SEG.A. 2023 Challenge -- A Data-Centric Approach for Segmenting the Aortic Vessel Tree: A Solution to SEG.A. Challenge 2023 Segmentation Task -- Automatic Aorta Segmentation with Heavily Augmented, High-Resolution 3-D ResUNet: Contribution to the SEG.A Challenge -- Position-encoded pixel-to-prototype contrastive learning for aortic vessel tree segmentation -- Misclassification Loss for Segmentation of the Aortic Vessel Tree -- Deep Learning-based segmentation and mesh reconstruction of the Aortic Vessel Tree from CTA images -- RASNet: U-Net-based Robust Aortic Segmentation Network For Multicenter Datasets -- Optimizing Aortic Segmentation with an Innovative Quality Assessment: The Role of Global Sensitivity Analysis -- A mini tutorial on mesh generation of blood vessels for CFD applications.
520 _aThis book constitutes the First Segmentation of the Aorta Challenge, SEG.A. 2023, which was held in conjunction with the 26th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2023, on October 8, 2023. The 8 full and 3 short papers presented have been carefully reviewed and selected for inclusion in the book. They focus specifically on robustness, visual quality and meshing of automatically generated segmentations of aortic vessel trees from CT imaging. The challenge was organized as a "container submission" challenge, where participants had to upload their algorithms to Grand Challenge in the form of Docker containers. Three tasks were created for SEG.A. 2023.
650 0 _aImage processing
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650 0 _aComputers.
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650 0 _aEducation
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650 1 4 _aComputer Imaging, Vision, Pattern Recognition and Graphics.
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650 2 4 _aImage Processing.
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650 2 4 _aComputer Application in Social and Behavioral Sciences.
_931815
650 2 4 _aComputing Milieux.
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650 2 4 _aComputers and Education.
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700 1 _aPepe, Antonio.
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700 1 _aMelito, Gian Marco.
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700 1 _aEgger, Jan.
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773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
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830 0 _aLecture Notes in Computer Science,
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856 4 0 _uhttps://doi.org/10.1007/978-3-031-53241-2
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