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Medical Computer Vision. Recognition Techniques and Applications in Medical Imaging [electronic resource] : International MICCAI Workshop, MCV 2010, Beijing, China, September 20, 2010, Revised Selected Papers / edited by Bjoern Menze, Georg Langs, Zhuowen Tu, Antonio Criminisi.

Por: Colaborador(es): Tipo de material: TextoTextoSeries Lecture Notes in Computer Science ; 6533 | Lecture Notes in Computer Science ; 6533Editor: Berlin, Heidelberg : Springer Berlin Heidelberg, 2011Descripción: XI, 226p. online resourceTipo de contenido:
  • text
Tipo de medio:
  • computer
Tipo de soporte:
  • online resource
ISBN:
  • 9783642184215
Trabajos contenidos:
  • SpringerLink (Online service)
Tema(s): Formatos físicos adicionales: Sin títuloClasificación CDD:
  • 006.6 23
  • 006.37 23
Clasificación LoC:
  • TA1637-1638
  • TA1637-1638
Recursos en línea: Springer eBooksResumen: This book constitutes the thoroughly refereed post-workshop proceedings of the International Workshop on Medical Computer Vision, MCV 2010, held in Beijing, China, in September 2010 as a satellite event of the 13th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2010. The 10 revised full papers and 11 revised poster papers presented were carefully reviewed and selected from 38 initial submissions. The papers explore the use of modern image recognition technology in tasks such as semantic anatomy parsing, automatic segmentation and quantification, anomaly detection and categorization, data harvesting, semantic navigation and visualization, data organization and clustering, and general-purpose automatic understanding of medical images.
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This book constitutes the thoroughly refereed post-workshop proceedings of the International Workshop on Medical Computer Vision, MCV 2010, held in Beijing, China, in September 2010 as a satellite event of the 13th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2010. The 10 revised full papers and 11 revised poster papers presented were carefully reviewed and selected from 38 initial submissions. The papers explore the use of modern image recognition technology in tasks such as semantic anatomy parsing, automatic segmentation and quantification, anomaly detection and categorization, data harvesting, semantic navigation and visualization, data organization and clustering, and general-purpose automatic understanding of medical images.

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