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Medical Computer Vision: Algorithms for Big Data [electronic resource] : International Workshop, MCV 2014, Held in Conjunction with MICCAI 2014, Cambridge, MA, USA, September 18, 2014, Revised Selected Papers /

Contributor(s): Material type: TextTextSeries: Image Processing, Computer Vision, Pattern Recognition, and Graphics ; 8848Publisher: Cham : Springer International Publishing : Imprint: Springer, 2014Edition: 1st ed. 2014Description: XI, 211 p. 78 illus. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783319139722
Subject(s): Additional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification:
  • 006.37 23
LOC classification:
  • TA1634
Online resources:
Contents:
Automatic segmentation and registration -- Localization of anatomical features -- Detection of anomalies.
In: Springer Nature eBookSummary: 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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Automatic segmentation and registration -- Localization of anatomical features -- Detection of anomalies.

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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