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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 / / edited by Bjoern Menze, Georg Langs, Albert Montillo, Michael Kelm, Henning Müller, Shaoting Zhang, Weidong (Tom) Cai, Dimitris Metaxas



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Titolo: 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 / / edited by Bjoern Menze, Georg Langs, Albert Montillo, Michael Kelm, Henning Müller, Shaoting Zhang, Weidong (Tom) Cai, Dimitris Metaxas Visualizza cluster
Pubblicazione: Cham : , : Springer International Publishing : , : Imprint : Springer, , 2014
Edizione: 1st ed. 2014.
Descrizione fisica: 1 online resource (XI, 211 p. 78 illus.)
Disciplina: 006.6
006.37
Soggetto topico: Optical data processing
Pattern recognition
User interfaces (Computer systems)
Computer graphics
Computer simulation
Image Processing and Computer Vision
Pattern Recognition
User Interfaces and Human Computer Interaction
Computer Graphics
Simulation and Modeling
Persona (resp. second.): MenzeBjoern
LangsGeorg
MontilloAlbert
KelmMichael
MüllerHenning
ZhangShaoting
CaiWeidong (Tom)
MetaxasDimitris
Note generali: Bibliographic Level Mode of Issuance: Monograph
Nota di contenuto: Automatic segmentation and registration -- Localization of anatomical features -- Detection of anomalies.
Sommario/riassunto: 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.
Titolo autorizzato: Medical Computer Vision: Algorithms for Big Data  Visualizza cluster
ISBN: 3-319-13972-X
Formato: Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione: Inglese
Record Nr.: 9910484494403321
Lo trovi qui: Univ. Federico II
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Serie: Image Processing, Computer Vision, Pattern Recognition, and Graphics ; ; 8848