000 04453nam a22005535i 4500
001 978-3-031-31778-1
003 DE-He213
005 20240730170016.0
007 cr nn 008mamaa
008 230504s2023 sz | s |||| 0|eng d
020 _a9783031317781
_9978-3-031-31778-1
024 7 _a10.1007/978-3-031-31778-1
_2doi
050 4 _aTA1501-1820
050 4 _aTA1634
072 7 _aUYT
_2bicssc
072 7 _aCOM016000
_2bisacsh
072 7 _aUYT
_2thema
082 0 4 _a006
_223
245 1 0 _aLeft Atrial and Scar Quantification and Segmentation
_h[electronic resource] :
_bFirst Challenge, LAScarQS 2022, Held in Conjunction with MICCAI 2022, Singapore, September 18, 2022, Proceedings /
_cedited by Xiahai Zhuang, Lei Li, Sihan Wang, Fuping Wu.
250 _a1st ed. 2023.
264 1 _aCham :
_bSpringer Nature Switzerland :
_bImprint: Springer,
_c2023.
300 _aX, 164 p. 83 illus., 72 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aLecture Notes in Computer Science,
_x1611-3349 ;
_v13586
505 0 _aLASSNet: A four steps deep neural network for Left Atrial Segmentation and Scar Quantification -- Multi-Depth Boundary-Aware Left Atrial Scar Segmentation Network -- Self Pre-training with Single-scale Adapter for Left Atrial Segmentation -- UGformer for Robust Left Atrium and Scar Segmentation Across Scanners -- Automatically Segmenting the Left Atrium and Scars from LGE-MRIs Using a boundary-focused nnU-Net -- Two Stage of Histogram Matching Augmentation for Domain Generalization : Application to Left Atrial Segmentation -- Sequential Segmentation of the Left Atrium and Atrial Scars Using a Multi-scale Weight Sharing Network and Boundary-based Processing -- LA-HRNet: High-resolution network for automatic left atrial segmentation in multi-center LEG MRI -- Edge-enhanced Features Guided Joint Segmentation and Quantification of Left Atrium and Scars in LGE MRI Images -- TESSLA: Two-Stage Ensemble Scar Segmentation for the Left Atrium -- Deep U-Net architecture with curriculum learning for leftatrial segmentation -- Cross-domain Segmentation of Left Atrium Based on Multi-scale Decision Level Fusion -- Using Polynomial Loss and Uncertainty Information for Robust Left Atrial and Scar Quantification and Segmentation -- Automated segmentation of the left atrium and scar using deep convolutional neural networks -- Automatic Semi-Supervised Left Atrial Segmentation using Deep-Supervision 3DResUnet with Pseudo Labeling Approach for LAScarQS 2022 Challenge.
520 _aThis book constitutes the First Left Atrial and Scar Quantification and Segmentation Challenge, LAScarQS 2022, which was held in conjunction with the 25th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2022, in Singapore, in September 2022. The 15 papers presented in this volume were carefully reviewed and selected form numerous submissions. The aim of the challenge is not only benchmarking various LA scar segmentation algorithms, but also covering the topic of general cardiac image segmentation, quantification, joint optimization, and model generalization, and raising discussions for further technical development and clinical deployment.
650 0 _aImage processing
_xDigital techniques.
_94145
650 0 _aComputer vision.
_991610
650 1 4 _aComputer Imaging, Vision, Pattern Recognition and Graphics.
_931569
700 1 _aZhuang, Xiahai.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_991611
700 1 _aLi, Lei.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_991612
700 1 _aWang, Sihan.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_991613
700 1 _aWu, Fuping.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_991614
710 2 _aSpringerLink (Online service)
_991615
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783031317774
776 0 8 _iPrinted edition:
_z9783031317798
830 0 _aLecture Notes in Computer Science,
_x1611-3349 ;
_v13586
_923263
856 4 0 _uhttps://doi.org/10.1007/978-3-031-31778-1
912 _aZDB-2-SCS
912 _aZDB-2-SXCS
912 _aZDB-2-LNC
942 _cELN
999 _c86678
_d86678