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Titlebook: Medical Image Computing and Computer Assisted Intervention – MICCAI 2022; 25th International C Linwei Wang,Qi Dou,Shuo Li Conference procee

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书目名称Medical Image Computing and Computer Assisted Intervention – MICCAI 2022
副标题25th International C
编辑Linwei Wang,Qi Dou,Shuo Li
视频video
丛书名称Lecture Notes in Computer Science
图书封面Titlebook: Medical Image Computing and Computer Assisted Intervention – MICCAI 2022; 25th International C Linwei Wang,Qi Dou,Shuo Li Conference procee
描述The eight-volume set LNCS 13431, 13432, 13433, 13434, 13435, 13436, 13437, and 13438 constitutes the refereed proceedings of the 25th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2022, which was held in Singapore in September 2022..The 574 revised full papers presented were carefully reviewed and selected from 1831 submissions in a double-blind review process. The papers are organized in the following topical sections:.Part I: Brain development and atlases; DWI and tractography; functional brain networks; neuroimaging; heart and lung imaging; dermatology;.Part II: Computational (integrative) pathology; computational anatomy and physiology; ophthalmology; fetal imaging;.Part III: Breast imaging; colonoscopy; computer aided diagnosis;.Part IV: Microscopic image analysis; positron emission tomography; ultrasound imaging; video data analysis; image segmentation I;.Part V: Image segmentation II; integration of imaging with non-imaging biomarkers;.Part VI: Image registration; image reconstruction;.Part VII: Image-Guided interventions and surgery; outcome and disease prediction; surgical data science; surgical planning and simulation; mach
出版日期Conference proceedings 2022
关键词artificial intelligence; bioinformatics; computer vision; deep learning; image analysis; image enhancemen
版次1
doihttps://doi.org/10.1007/978-3-031-16446-0
isbn_softcover978-3-031-16445-3
isbn_ebook978-3-031-16446-0Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
The information of publication is updating

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978-3-031-16445-3The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
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Unsupervised Deformable Image Registration with Absent Correspondences in Pre-operative and Post-recs on 3D clinical data from the BraTS-Reg challenge demonstrate our method can improve image alignment compared to traditional and deep learning-based registration approaches with or without cost function masking strategy. The source code is available at ..
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ContraReg: Contrastive Learning of Multi-modality Unsupervised Deformable Image Registrationtally, ContraReg achieves accurate and robust results with smooth and invertible deformations across a series of baselines and ablations on a neonatal T1-T2 brain MRI registration task with all methods validated over a wide range of deformation regularization strengths.
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Learning-Based US-MR Liver Image Registration with Spatial Priorstechnique. This workflow was validated with . liver image data for 18 subjects. The best average TRE of rigid and non-rigid registration obtained with our dataset was at 6.27 ± 2.82 mm and 3.63 ± 1.87 mm, respectively.
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0302-9743 ational Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2022, which was held in Singapore in September 2022..The 574 revised full papers presented were carefully reviewed and selected from 1831 submissions in a double-blind review process. The papers are organized in
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