Medical Image Computing and Computer-Assisted Intervention – MICCAI 2011 [electronic resource] : 14th International Conference, Toronto, Canada, September 18-22, 2011, Proceedings, Part III / edited by Gabor Fichtinger, Anne Martel, Terry Peters.
By: Fichtinger, Gabor [editor.].
Contributor(s): Martel, Anne [editor.] | Peters, Terry [editor.] | SpringerLink (Online service).
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BookSeries: Lecture Notes in Computer Science: 6893Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg, 2011Description: XXXI, 685 p. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783642236266.Subject(s): Computer science | Medical records -- Data processing | Radiology, Medical | Artificial intelligence | Computer graphics | Computer vision | Optical pattern recognition | Computer Science | Image Processing and Computer Vision | Pattern Recognition | Computer Graphics | Artificial Intelligence (incl. Robotics) | Imaging / Radiology | Health InformaticsDDC classification: 006.6 | 006.37 Online resources: Click here to access online
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Springer eBooksSummary: The three-volume set LNCS 6891, 6892 and 6893 constitutes the refereed proceedings of the 14th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2011, held in Toronto, Canada, in September 2011. Based on rigorous peer reviews, the program committee carefully selected 251 revised papers from 819 submissions for presentation in three volumes. The third volume includes 82 papers organized in topical sections on computer-aided diagnosis and machine learning, and segmentation.
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The three-volume set LNCS 6891, 6892 and 6893 constitutes the refereed proceedings of the 14th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2011, held in Toronto, Canada, in September 2011. Based on rigorous peer reviews, the program committee carefully selected 251 revised papers from 819 submissions for presentation in three volumes. The third volume includes 82 papers organized in topical sections on computer-aided diagnosis and machine learning, and segmentation.
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