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Record Nr. |
UNINA9910483240703321 |
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Titolo |
Medical Image Computing and Computer-Assisted Intervention – MICCAI 2016 : 19th International Conference, Athens, Greece, October 17-21, 2016, Proceedings, Part I / / edited by Sebastien Ourselin, Leo Joskowicz, Mert R. Sabuncu, Gozde Unal, William Wells |
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Pubbl/distr/stampa |
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016 |
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ISBN |
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Edizione |
[1st ed. 2016.] |
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Descrizione fisica |
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1 online resource (XLIV, 681 p. 273 illus., 269 illus. in color.) |
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Collana |
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Image Processing, Computer Vision, Pattern Recognition, and Graphics ; ; 9900 |
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Disciplina |
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Soggetti |
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Computer vision |
Pattern recognition systems |
Computer graphics |
Artificial intelligence |
Radiology |
Medical informatics |
Computer Vision |
Automated Pattern Recognition |
Computer Graphics |
Artificial Intelligence |
Health Informatics |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di bibliografia |
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Includes bibliographical references and index. |
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Nota di contenuto |
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Brain analysis -- Brain analysis - connectivity -- Brain analysis - cortical morphology -- Alzheimer disease -- Surgical guidance and tracking -- Computer aided interventions -- Ultrasound image analysis -- cancer image analysis. |
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Sommario/riassunto |
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The three-volume set LNCS 9900, 9901, and 9902 constitutes the refereed proceedings of the 19th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2016, held in Athens, Greece, in October 2016. Based on rigorous peer reviews, the program committee carefully selected 228 revised regular |
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papers from 756 submissions for presentation in three volumes. The papers have been organized in the following topical sections: Part I: brain analysis; brain analysis - connectivity; brain analysis - cortical morphology; Alzheimer disease; surgical guidance and tracking; computer aided interventions; ultrasound image analysis; cancer image analysis; Part II: machine learning and feature selection; deep learning in medical imaging; applications of machine learning; segmentation; cell image analysis; Part III: registration and deformation estimation; shape modeling; cardiac and vascular image analysis; image reconstruction; and MR image analysis. |
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