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Titlebook: Cloud-Based Benchmarking of Medical Image Analysis; Allan Hanbury,Henning Müller,Georg Langs Book‘‘‘‘‘‘‘‘ 2017 The Editor(s) (if applicabl

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书目名称Cloud-Based Benchmarking of Medical Image Analysis
编辑Allan Hanbury,Henning Müller,Georg Langs
视频video
概述Presents innovative, cloud-based medical image analysis benchmarks.Highlights both the basic paradigm of Evaluation-as-a-Service and its application.Appeals to medical imaging researchers as well as d
图书封面Titlebook: Cloud-Based Benchmarking of Medical Image Analysis;  Allan Hanbury,Henning Müller,Georg Langs Book‘‘‘‘‘‘‘‘ 2017 The Editor(s) (if applicabl
描述This book is open access under a CC BY-NC 2.5 license..This book presents the VISCERAL project benchmarks for analysis and retrieval of 3D medical images (CT and MRI) on a large scale, which used an innovative cloud-based evaluation approach where the image data were stored centrally on a cloud infrastructure and participants placed their programs in virtual machines on the cloud. The book presents the points of view of both the organizers of the VISCERAL benchmarks and the participants..The book is divided into five parts. Part I presents the cloud-based benchmarking and Evaluation-as-a-Service paradigm that the VISCERAL benchmarks used. Part II focuses on the datasets of medical images annotated with ground truth created in VISCERAL that continue to be available for research. It also covers the practical aspects of obtaining permission to use medical data and manually annotating 3D medical images efficiently and effectively. The VISCERAL benchmarks are described in Part III, including a presentation and analysis of metrics used in evaluation of medical image analysis and search. Lastly, Parts IV and V present reports by some of the participants in the VISCERAL benchmarks, with Pa
出版日期Book‘‘‘‘‘‘‘‘ 2017
关键词Image Processing; Image Search; Health Informatics; Medical Sciences; Performance Evaluation; Cloud Compu
版次1
doihttps://doi.org/10.1007/978-3-319-49644-3
isbn_softcover978-3-319-84207-3
isbn_ebook978-3-319-49644-3
copyrightThe Editor(s) (if applicable) and The Author(s) 2017
The information of publication is updating

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Using the Cloud as a Platform for Evaluation and Data Preparation GitHub. The system can be accessed by both participants and administrators, reducing the direct participant–organizer interaction and handling the documentation available for each of the benchmarks organized by VISCERAL. Also, the upload of the VISCERAL usage and participation agreements is integra
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Ethical and Privacy Aspects of Using Medical Image Data creation of a benchmark for organ segmentation, landmark detection, lesion detection and similar case retrieval. The availability of a large amount of imaging data was extremely important for the project goals, and thus, we present an analysis of the procedures that were followed for getting access
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Datasets Created in VISCERALets were used for training and evaluation of participant algorithms in the VISCERAL Benchmarks. In addition to Gold Corpus datasets, the architecture of VISCERAL enables the creation of . annotations of far larger datasets, which are generated by the collective ensemble of submitted algorithms. In t
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Automatic Atlas-Free Multiorgan Segmentation of Contrast-Enhanced CT Scansr large-scale content-based image retrieval (CBIR). Many existing segmentation methods are tailored to a single structure and/or require an atlas, which entails multistructure deformable registration and is time-consuming. We present a fully automatic atlas-free segmentation of multiple organs of th
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