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Titlebook: Medical Image Computing and Computer Assisted Intervention – MICCAI 2020; 23rd International C Anne L. Martel,Purang Abolmaesumi,Leo Joskow

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书目名称Medical Image Computing and Computer Assisted Intervention – MICCAI 2020
副标题23rd International C
编辑Anne L. Martel,Purang Abolmaesumi,Leo Joskowicz
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 2020; 23rd International C Anne L. Martel,Purang Abolmaesumi,Leo Joskow
描述The seven-volume set LNCS 12261, 12262, 12263, 12264, 12265, 12266, and 12267 constitutes the refereed proceedings of the 23rd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2020, held in Lima, Peru, in October 2020. The conference was held virtually due to the COVID-19 pandemic..The 542 revised full papers presented were carefully reviewed and selected from 1809 submissions in a double-blind review process. The papers are organized in the following topical sections:..Part I: machine learning methodologies..Part II: image reconstruction; prediction and diagnosis; cross-domain methods and reconstruction; domain adaptation; machine learning applications; generative adversarial networks..Part III: CAI applications; image registration; instrumentation and surgical phase detection; navigation and visualization; ultrasound imaging; video image analysis..Part IV: segmentation; shape models and landmark detection..Part V: biological, optical, microscopic imaging; cell segmentation and stain normalization; histopathology image analysis; opthalmology..Part VI: angiography and vessel analysis; breast imaging; colonoscopy; dermatology; fetal imag
出版日期Conference proceedings 2020
关键词artificial intelligence; bioinformatics; color image processing; computer aided diagnosis; computer visi
版次1
doihttps://doi.org/10.1007/978-3-030-59713-9
isbn_softcover978-3-030-59712-2
isbn_ebook978-3-030-59713-9Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer Nature Switzerland AG 2020
The information of publication is updating

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978-3-030-59712-2Springer Nature Switzerland AG 2020
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https://doi.org/10.1007/978-3-030-59713-9artificial intelligence; bioinformatics; color image processing; computer aided diagnosis; computer visi
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Active MR ,-space Sampling with Reinforcement Learningion process and propose the use of reinforcement learning to solve it. Experiments on a large scale public MRI dataset of knees show that our proposed models significantly outperform the state-of-the-art in active MRI acquisition, over a large range of acceleration factors.
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End-to-End Variational Networks for Accelerated MRI Reconstructionemained an open problem. In this paper, we present a new approach to this problem that extends previously proposed variational methods by learning fully end-to-end. Our method obtains new state-of-the-art results on the fastMRI dataset [.] for both brain and knee MRIs.
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Acceleration of High-Resolution 3D MR Fingerprinting via a Graph Convolutional Network-based convolutional neural network that caters to non-Cartesian spiral trajectories commonly used for MRF acquisition. We improve tissue quantification accuracy compared with the state of the art. Our method enables fast 3D MRF with high spatial resolution, allowing whole-brain coverage within 5 min, making MRF more feasible in clinical settings.
发表于 2025-3-23 07:56:01 | 显示全部楼层
Conference proceedings 2020e on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2020, held in Lima, Peru, in October 2020. The conference was held virtually due to the COVID-19 pandemic..The 542 revised full papers presented were carefully reviewed and selected from 1809 submissions in a double-blind review
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