1.

Record Nr.

UNINA9910484494403321

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

Pubbl/distr/stampa

Cham : , : Springer International Publishing : , : Imprint : Springer, , 2014

ISBN

3-319-13972-X

Edizione

[1st ed. 2014.]

Descrizione fisica

1 online resource (XI, 211 p. 78 illus.)

Collana

Image Processing, Computer Vision, Pattern Recognition, and Graphics ; ; 8848

Disciplina

006.6

006.37

Soggetti

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

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

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.