Medical Content-Based Retrieval for Clinical Decision Support [E-Book] : Third MICCAI International Workshop, MCBR-CDS 2012, Nice, France, October 1, 2012, Revised Selected Papers / edited by Hayit Greenspan, Henning Müller, Tanveer Syeda-Mahmood.
This book constitutes the refereed proceedings of the Third MICCAI Workshop on Medical Content-Based Retrieval for Clinical Decision Support, MCBR-CBS 2012, held in Nice, France, in October 2012.The 10 revised full papers presented together with 2 invited talks were carefully reviewed and selected f...
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Full text |
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Personal Name(s): | Greenspan, Hayit. |
Müller, Henning. / Syeda-Mahmood, Tanveer. | |
Imprint: |
Berlin, Heidelberg :
Springer,
2013
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Physical Description: |
VIII, 145 p. 41 illus. digital. |
Note: |
englisch |
ISBN: |
9783642366789 |
DOI: |
10.1007/978-3-642-36678-9 |
Series Title: |
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Lecture notes in computer science ;
7723 |
Subject (LOC): |
- Workshop Overview
- Overview of the Third Workshop on Medical Content–Based Retrieval for Clinical Decision Support (MCBR–CDS 2012)
- Invited Talk
- A Polynomial Model of Surgical Gestures for Real-Time Retrieval of Surgery Videos
- Methods
- Exploiting 3D Part-Based Analysis, Description and Indexing to Support Medical Applications
- Skull Retrieval for Craniosynostosis Using Sparse Logistic Regression Models
- 3D/4D Data Retrieval
- Retrieval of 4D Dual Energy CT for Pulmonary Embolism Diagnosis
- Immediate ROI Search for 3-D Medical Images
- The Synergy of 3D SIFT and Sparse Codes for Classification of Viewpoints from Echocardiogram Videos
- Assessing the Classification of Liver Focal Lesions by Using Multi-phase Computer Tomography Scans
- Invited Talk
- VISCERAL: Towards Large Data in Medical Imaging — Challenges and Directions
- Visual Features
- Customised Frequency Pre-filtering in a Local Binary Pattern-Based Classification of Gastrointestinal Images
- Bag–of–Colors for Biomedical Document Image Classification
- Multimodal Retrieval
- An SVD–Bypass Latent Semantic Analysis for Image Retrieval
- Multimedia Retrieval in a Medical Image Collection: Results Using Modality Classes.