Benutzerdefiniertes Cover
Benutzerdefiniertes Cover
Normale Ansicht MARC ISBD

Medical Computer Vision: Algorithms for Big Data : International Workshop, MCV 2015, Held in Conjunction with MICCAI 2015, Munich, Germany, October 9, 2015, Revised Selected Papers / edited by Bjoern Menze, Georg Langs, Albert Montillo, Michael Kelm, Henning Müller, Shaoting Zhang, Weidong Cai, Dimitris Metaxas

Mitwirkende(r): Resource type: Ressourcentyp: Buch (Online)Buch (Online)Sprache: Englisch Reihen: SpringerLink Bücher | Springer eBook Collection Computer Science | Lecture notes in computer science ; 9601Verlag: Cham : Springer, 2016Beschreibung: Online-Ressource (XV, 182 p. 70 illus, online resource)ISBN:
  • 9783319420165
Schlagwörter: Andere physische Formen: 9783319420158 | Erscheint auch als: 978-3-319-42015-8 Druck-Ausgabe | Printed edition: 9783319420158 DDC-Klassifikation:
  • 006.6
  • 006.37
LOC-Klassifikation:
  • TA1637-1638 TA1634
  • TA1637-1638
  • TA1634
DOI: DOI: 10.1007/978-3-319-42016-5Online-Ressourcen: Zusammenfassung: This book constitutes the thoroughly refereed prost-workshop proceedings of the International Workshop on Medical Computer Vision: Algorithms for Big Data, MCS 2015, held in Munich, Germany, in October 2015, held in conjunction with the 18th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2015. The workshop shows well the current trends and tendencies in medical computer vision and how the techniques can be used in clinical work and on large data sets. It is organized in the following sections: predicting disease; atlas exploitation and avoidance; machine learning based analyses; advanced methods for image analysis; poster sessions. The 10 full, 5 short, 1 invited papers and one overview paper presented in this volume were carefully reviewed and selected from 22 submissionsZusammenfassung: Pedicting disease -- Atlas exploitation and avoidance -- Machine learning based analyses -- Advanced methods for image analysis -- Poster sessionsPPN: PPN: 1658456157Package identifier: Produktsigel: ZDB-2-LNC | ZDB-2-SCS | ZDB-2-SXCS | ZDB-2-SEB
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