Cloud-Based Benchmarking of Medical Image Analysis
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…
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Produktdetails
Weitere Autoren: Langs, Georg (Hrsg.) / Müller, Henning (Hrsg.)
- ISBN: 978-3-319-84207-3
- EAN: 9783319842073
- Produktnummer: 28480965
- Verlag: Springer International Publishing
- Sprache: Englisch
- Erscheinungsjahr: 2018
- Seitenangabe: 272 S.
- Masse: H23.5 cm x B15.5 cm x D1.4 cm 417 g
- Auflage: Softcover reprint of the original 1st ed. 2017
- Abbildungen: Paperback
- Gewicht: 417
Über den Autor
Allan Hanbury is Senior Researcher at the TU Wien, Austria, and was the coordinator of the EU-funded VISCERAL project on evaluation of algorithms on big data. His research interests include data science, information retrieval, multimodal information retrieval, and the evaluation of information retrieval systems and algorithms. Henning Müller is professor in computer sciences at the HES-SO, Sierre, Switzerland and in medicine at the University of Geneva, Switzerland. His research focuses on medical information retrieval, the organization of data science challenges and multimodal data analysis for big data and the underlying computing infrastructures. Georg Langs is the Head of the Computational Imaging Research Lab (CIR) at the Medical University of Vienna, Austria, and is also affiliated with the Medical Vision Group at CSAIL, Massachusetts Institute of Technology, USA. His main research interests are in neuroimaging, machine learning and medical image analysis.
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