Medical Content-Based Retrieval for Clinical Decision Support Third MICCAI International Workshop, MCBR-CDS 2012, Nice, France, October 1st, 2012, Revised Selected Papers /
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...
Clasificación: | Libro Electrónico |
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Autor Corporativo: | |
Otros Autores: | , , |
Formato: | Electrónico eBook |
Idioma: | Inglés |
Publicado: |
Berlin, Heidelberg :
Springer Berlin Heidelberg : Imprint: Springer,
2013.
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Edición: | 1st ed. 2013. |
Colección: | Image Processing, Computer Vision, Pattern Recognition, and Graphics ;
7723 |
Temas: | |
Acceso en línea: | Texto Completo |
Tabla de Contenidos:
- 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.