LEADER 04451nam 22006495 450 001 9910720070703321 005 20250319164347.0 010 $a9783031317781 010 $a3031317785 024 7 $a10.1007/978-3-031-31778-1 035 $a(MiAaPQ)EBC7246023 035 $a(Au-PeEL)EBL7246023 035 $a(DE-He213)978-3-031-31778-1 035 $a(OCoLC)1378743247 035 $a(PPN)270612122 035 $a(CKB)26581855700041 035 $a(EXLCZ)9926581855700041 100 $a20230504d2023 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aLeft Atrial and Scar Quantification and Segmentation $eFirst Challenge, LAScarQS 2022, Held in Conjunction with MICCAI 2022, Singapore, September 18, 2022, Proceedings /$fedited by Xiahai Zhuang, Lei Li, Sihan Wang, Fuping Wu 205 $a1st ed. 2023. 210 1$aCham :$cSpringer Nature Switzerland :$cImprint: Springer,$d2023. 215 $a1 online resource (174 pages) 225 1 $aLecture Notes in Computer Science,$x1611-3349 ;$v13586 311 08$aPrint version: Zhuang, Xiahai Left Atrial and Scar Quantification and Segmentation Cham : Springer,c2023 9783031317774 327 $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. 330 $aThis book constitutes the First Left Atrial and Scar Quantification and Segmentation Challenge, LAScarQS 2022, which was held in conjunction with the 25th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2022, in Singapore, in September 2022. The 15 papers presented in this volume were carefully reviewed and selected form numerous submissions. The aim of the challenge is not only benchmarking various LA scar segmentation algorithms, but also covering the topic of general cardiac image segmentation, quantification, joint optimization, and model generalization, and raising discussions for further technical development and clinical deployment. 410 0$aLecture Notes in Computer Science,$x1611-3349 ;$v13586 606 $aImage processing$xDigital techniques 606 $aComputer vision 606 $aComputer Imaging, Vision, Pattern Recognition and Graphics 606 $aCor$2thub 606 $aVisió per ordinador$2thub 608 $aCongressos$2thub 608 $aLlibres electrònics$2thub 615 0$aImage processing$xDigital techniques. 615 0$aComputer vision. 615 14$aComputer Imaging, Vision, Pattern Recognition and Graphics. 615 7$aCor 615 7$aVisió per ordinador 676 $a006 676 $a616.120754 700 $aZhuang$b Xiahai$01355673 701 $aLi$b Lei$01255050 701 $aWang$b Sihan$01355674 701 $aWu$b Fuping$01355675 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910720070703321 996 $aLeft Atrial and Scar Quantification and Segmentation$93359797 997 $aUNINA