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Medical Computer Vision Algorithms For Big Data International Workshop Mcv 2014 Held In Conjunction With Miccai 2014 Cambridge Ma Usa September 18 2014 Revised Selected Papers 1st Edition Bjoern Menze

  • SKU: BELL-4973824
Medical Computer Vision Algorithms For Big Data International Workshop Mcv 2014 Held In Conjunction With Miccai 2014 Cambridge Ma Usa September 18 2014 Revised Selected Papers 1st Edition Bjoern Menze
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Medical Computer Vision Algorithms For Big Data International Workshop Mcv 2014 Held In Conjunction With Miccai 2014 Cambridge Ma Usa September 18 2014 Revised Selected Papers 1st Edition Bjoern Menze instant download after payment.

Publisher: Springer International Publishing
File Extension: PDF
File size: 38.71 MB
Pages: 211
Author: Bjoern Menze, Georg Langs, Albert Montillo, Michael Kelm, Henning Müller, Shaoting Zhang, Weidong (Tom) Cai, Dimitris Metaxas (eds.)
ISBN: 9783319139715, 3319139711
Language: English
Year: 2014
Edition: 1

Product desciption

Medical Computer Vision Algorithms For Big Data International Workshop Mcv 2014 Held In Conjunction With Miccai 2014 Cambridge Ma Usa September 18 2014 Revised Selected Papers 1st Edition Bjoern Menze by Bjoern Menze, Georg Langs, Albert Montillo, Michael Kelm, Henning Müller, Shaoting Zhang, Weidong (tom) Cai, Dimitris Metaxas (eds.) 9783319139715, 3319139711 instant download after payment.

This book constitutes the thoroughly refereed post-workshop proceedings of the International Workshop on Medical Computer Vision: Algorithms for Big Data, MCV 2014, held in Cambridge, MA, USA, in September 2019, in conjunction with the 17th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2014. The one-day workshop aimed at exploring the use of modern computer vision technology and "big data" algorithms in tasks such as automatic segmentation and registration, localization of anatomical features and detection of anomalies emphasizing questions of harvesting, organizing and learning from large-scale medical imaging data sets and general-purpose automatic understanding of medical images. The 18 full and 1 short papers presented in this volume were carefully reviewed and selected from 30 submission.

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