Titlebook: Left Atrial and Scar Quantification and Segmentation; First Challenge, LAS Xiahai Zhuang,Lei Li,Fuping Wu Conference proceedings 2023 The E

不友善

书目名称Left Atrial and Scar Quantification and Segmentation影响因子(影响力)




书目名称Left Atrial and Scar Quantification and Segmentation影响因子(影响力)学科排名




书目名称Left Atrial and Scar Quantification and Segmentation网络公开度




书目名称Left Atrial and Scar Quantification and Segmentation网络公开度学科排名




书目名称Left Atrial and Scar Quantification and Segmentation被引频次




书目名称Left Atrial and Scar Quantification and Segmentation被引频次学科排名




书目名称Left Atrial and Scar Quantification and Segmentation年度引用




书目名称Left Atrial and Scar Quantification and Segmentation年度引用学科排名




书目名称Left Atrial and Scar Quantification and Segmentation读者反馈




书目名称Left Atrial and Scar Quantification and Segmentation读者反馈学科排名

船员

978-3-031-31777-4The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl

婴儿

Left Atrial and Scar Quantification and Segmentation978-3-031-31778-1Series ISSN 0302-9743 Series E-ISSN 1611-3349

剧毒

https://doi.org/10.1007/978-3-031-31778-1image processing; pattern recognition; image segmentation; artificial intelligence; computer vision; medi

无孔

脱落

0302-9743 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 benchmarkin

Veneer

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

expansive

,Sequential Segmentation of the Left Atrium and Atrial Scars Using a Multi-scale Weight Sharing Netwage Dice score of 0.938 and 0.558 for the LA cavity and scars segmentation of task 1, and a Dice score of 0.846 for LA cavity segmentation of task 2. The pre-trained models, source code, and implementation details are available at

浮雕

Multi-depth Boundary-Aware Left Atrial Scar Segmentation Network,ated from the LA branch to the scar branch. Thus, LA scar segmentation can be performed condition on the LA boundaries regions. In our experiments, 40 labeled images were used to train the proposed network, and the remaining 20 labeled images were used for evaluation. The network achieved an average Dice score of 0.608 for LA scar segmentation.

不公开

,Two Stage of Histogram Matching Augmentation for Domain Generalization: Application to Left Atrial The method is evaluated on LAScarQS 2022 data-set, acquiring average Dice of 0.87790 for LA segmentation. Besides, the two-stage network is about four times faster against a single-stage network in the test phase.