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Medical Content-Based Retrieval for Clinical Decision Support: First MICCAI International Workshop, MCBR-CBS 2009, London, UK, September 20, 2009. Revised Selected Papers - Couverture souple
Synopsis
We are pleased to present this set of peer-reviewed papers from the ?rst MICCAI Workshop on Medical Content-Based Retrieval for Clinical Decision Support. The MICCAI conference has been the ?agship conference for the m- ical imaging community re?ecting the state of the art in techniques of segm- tation, registration, and robotic surgery. Yet, the transfer of these techniques to clinical practice is rarely discussed in the MICCAI conference. To address this gap, we proposed to hold this workshop with MICCAI in London in September 2009. The goal of the workshop was to show the application of content-based retrieval in clinical decision support. With advances in electronic patient record systems, a large number of pre-diagnosed patient data sets are now bec- ing available. These data sets are often multimodal consisting of images (x-ray, CT, MRI), videos and other time series, and textual data (free text reports and structuredclinicaldata). Analyzing thesemultimodalsourcesfordisease-speci?c information across patients can reveal important similarities between patients and hence their underlying diseases and potential treatments. Researchers are now beginning to use techniques of content-based retrieval to search for disea- speci?c information in modalities to ?nd supporting evidence for a disease or to automatically learn associations of symptoms and diseases. Benchmarking frameworks such as ImageCLEF (Image retrieval track in the Cross-Language Evaluation Forum) have expanded over the past ?ve years to include large m- ical image collections for testing various algorithms for medical image retrieval and classi?cation.
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- ÉditeurSpringer
- Date d'édition2010
- ISBN 10 3642117686
- ISBN 13 9783642117688
- ReliureBroché
- Langueanglais
- Numéro d'édition1
- Nombre de pages136
- ÉditeurMüller Henning, Syeda-Mahmood Tanveer, Duncan James, Wang Fei, Kalpathy-Cramer Jayashree
- Coordonnées du fabricantnon disponible
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Medical Content-Based Retrieval for Clinical Decision Support : First MICCAI International Workshop, MCBR-CBS 2009, London, UK, September 20, 2009. Revised Selected Papers
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Springer Berlin Heidelberg, 2010
ISBN 10 : 3642117686
ISBN 13 : 9783642117688
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MEDICAL CONTENT-BASED RETRIEVAL FOR CLINICAL DECISION SUPPORT: FIRST MICCAI WORKSHOP, MCBR- CBS 2009, LONDON, UK, SEPTEMBER 20, 2009. REVISED SELECTED
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Medical Content-Based Retrieval for Clinical Decision Support : First MICCAI International Workshop, MCBR-CBS 2009, London, UK, September 20, 2009. Revised Selected Papers
Edité par
Springer Berlin Heidelberg, 2010
ISBN 10 : 3642117686
ISBN 13 : 9783642117688
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Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - We are pleased to present this set of peer-reviewed papers from the rst MICCAI Workshop on Medical Content-Based Retrieval for Clinical Decision Support. The MICCAI conference has been the agship conference for the m- ical imaging community re ecting the state of the art in techniques of segm- tation, registration, and robotic surgery. Yet, the transfer of these techniques to clinical practice is rarely discussed in the MICCAI conference. To address this gap, we proposed to hold this workshop with MICCAI in London in September 2009. The goal of the workshop was to show the application of content-based retrieval in clinical decision support. With advances in electronic patient record systems, a large number of pre-diagnosed patient data sets are now bec- ing available. These data sets are often multimodal consisting of images (x-ray, CT, MRI), videos and other time series, and textual data (free text reports and structuredclinicaldata). Analyzing thesemultimodalsourcesfordisease-speci c information across patients can reveal important similarities between patients and hence their underlying diseases and potential treatments. Researchers are now beginning to use techniques of content-based retrieval to search for disea- speci c information in modalities to nd supporting evidence for a disease or to automatically learn associations of symptoms and diseases. Benchmarking frameworks such as ImageCLEF (Image retrieval track in the Cross-Language Evaluation Forum) have expanded over the past ve years to include large m- ical image collections for testing various algorithms for medical image retrieval and classi cation. N° de réf. du vendeur 9783642117688
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Medical Content-Based Retrieval for Clinical Decision Support
Edité par
Springer Berlin Heidelberg Feb 2010, 2010
ISBN 10 : 3642117686
ISBN 13 : 9783642117688
Neuf
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Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -We are pleased to present this set of peer-reviewed papers from the rst MICCAI Workshop on Medical Content-Based Retrieval for Clinical Decision Support. The MICCAI conference has been the agship conference for the m- ical imaging community re ecting the state of the art in techniques of segm- tation, registration, and robotic surgery. Yet, the transfer of these techniques to clinical practice is rarely discussed in the MICCAI conference. To address this gap, we proposed to hold this workshop with MICCAI in London in September 2009. The goal of the workshop was to show the application of content-based retrieval in clinical decision support. With advances in electronic patient record systems, a large number of pre-diagnosed patient data sets are now bec- ing available. These data sets are often multimodal consisting of images (x-ray, CT, MRI), videos and other time series, and textual data (free text reports and structuredclinicaldata). Analyzing thesemultimodalsourcesfordisease-speci c information across patients can reveal important similarities between patients and hence their underlying diseases and potential treatments. Researchers are now beginning to use techniques of content-based retrieval to search for disea- speci c information in modalities to nd supporting evidence for a disease or to automatically learn associations of symptoms and diseases. Benchmarking frameworks such as ImageCLEF (Image retrieval track in the Cross-Language Evaluation Forum) have expanded over the past ve years to include large m- ical image collections for testing various algorithms for medical image retrieval and classi cation. 136 pp. Englisch. N° de réf. du vendeur 9783642117688
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Medical Content-Based Retrieval for Clinical Decision Support
Edité par
Springer Berlin Heidelberg, Springer Berlin Heidelberg Feb 2010, 2010
ISBN 10 : 3642117686
ISBN 13 : 9783642117688
Neuf
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Taschenbuch. Etat : Neu. Neuware -We are pleased to present this set of peer-reviewed papers from the rst MICCAI Workshop on Medical Content-Based Retrieval for Clinical Decision Support. The MICCAI conference has been the agship conference for the m- ical imaging community re ecting the state of the art in techniques of segm- tation, registration, and robotic surgery. Yet, the transfer of these techniques to clinical practice is rarely discussed in the MICCAI conference. To address this gap, we proposed to hold this workshop with MICCAI in London in September 2009. The goal of the workshop was to show the application of content-based retrieval in clinical decision support. With advances in electronic patient record systems, a large number of pre-diagnosed patient data sets are now bec- ing available. These data sets are often multimodal consisting of images (x-ray, CT, MRI), videos and other time series, and textual data (free text reports and structuredclinicaldata). Analyzing thesemultimodalsourcesfordisease-speci c information across patients can reveal important similarities between patients and hence their underlying diseases and potential treatments. Researchers are now beginning to use techniques of content-based retrieval to search for disea- speci c information in modalities to nd supporting evidence for a disease or to automatically learn associations of symptoms and diseases. Benchmarking frameworks such as ImageCLEF (Image retrieval track in the Cross-Language Evaluation Forum) have expanded over the past ve years to include large m- ical image collections for testing various algorithms for medical image retrieval and classi cation.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 136 pp. Englisch. N° de réf. du vendeur 9783642117688
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Medical Content-Based Retrieval for Clinical Decision Support
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ISBN 13 : 9783642117688
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Medical Content-Based Retrieval for Clinical Decision Support: First MICCAI International Workshop, MCBR-CBS 2009, London, UK, September 20, 2009. ... (Lecture Notes in Computer Science, 5853)
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Medical Content-Based Retrieval for Clinical Decision Support: First MICCAI International Workshop, MCBR-CBS 2009, London, UK, September 20, 2009. Revised Selected Papers (Lecture Notes in Computer Science / Image Processing, Computer Vision, Pattern Reco
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