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Prototypes for Content-Based Image Retrieval in Clinical Practice
Content-based image retrieval (CBIR) has been proposed as key technology for computer-aided diagnostics (CAD). This paper reviews the state of the art and future challenges in CBIR for CAD applied to clinical practice. We define applicability to clinical practice by having recently demonstrated the...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Bentham Open
2011
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3149811/ https://www.ncbi.nlm.nih.gov/pubmed/21892374 http://dx.doi.org/10.2174/1874431101105010058 |
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author | Depeursinge, Adrien Fischer, Benedikt Müller, Henning Deserno, Thomas M |
author_facet | Depeursinge, Adrien Fischer, Benedikt Müller, Henning Deserno, Thomas M |
author_sort | Depeursinge, Adrien |
collection | PubMed |
description | Content-based image retrieval (CBIR) has been proposed as key technology for computer-aided diagnostics (CAD). This paper reviews the state of the art and future challenges in CBIR for CAD applied to clinical practice. We define applicability to clinical practice by having recently demonstrated the CBIR system on one of the CAD demonstration workshops held at international conferences, such as SPIE Medical Imaging, CARS, SIIM, RSNA, and IEEE ISBI. From 2009 to 2011, the programs of CADdemo@CARS and the CAD Demonstration Workshop at SPIE Medical Imaging were sought for the key word “retrieval” in the title. The systems identified were analyzed and compared according to the hierarchy of gaps for CBIR systems. In total, 70 software demonstrations were analyzed. 5 systems were identified meeting the criterions. The fields of application are (i) bone age assessment, (ii) bone fractures, (iii) interstitial lung diseases, and (iv) mammography. Bridging the particular gaps of semantics, feature extraction, feature structure, and evaluation have been addressed most frequently. In specific application domains, CBIR technology is available for clinical practice. While system development has mainly focused on bridging content and feature gaps, performance and usability have become increasingly important. The evaluation must be based on a larger set of reference data, and workflow integration must be achieved before CBIR-CAD is really established in clinical practice. |
format | Online Article Text |
id | pubmed-3149811 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2011 |
publisher | Bentham Open |
record_format | MEDLINE/PubMed |
spelling | pubmed-31498112011-09-02 Prototypes for Content-Based Image Retrieval in Clinical Practice Depeursinge, Adrien Fischer, Benedikt Müller, Henning Deserno, Thomas M Open Med Inform J Article Content-based image retrieval (CBIR) has been proposed as key technology for computer-aided diagnostics (CAD). This paper reviews the state of the art and future challenges in CBIR for CAD applied to clinical practice. We define applicability to clinical practice by having recently demonstrated the CBIR system on one of the CAD demonstration workshops held at international conferences, such as SPIE Medical Imaging, CARS, SIIM, RSNA, and IEEE ISBI. From 2009 to 2011, the programs of CADdemo@CARS and the CAD Demonstration Workshop at SPIE Medical Imaging were sought for the key word “retrieval” in the title. The systems identified were analyzed and compared according to the hierarchy of gaps for CBIR systems. In total, 70 software demonstrations were analyzed. 5 systems were identified meeting the criterions. The fields of application are (i) bone age assessment, (ii) bone fractures, (iii) interstitial lung diseases, and (iv) mammography. Bridging the particular gaps of semantics, feature extraction, feature structure, and evaluation have been addressed most frequently. In specific application domains, CBIR technology is available for clinical practice. While system development has mainly focused on bridging content and feature gaps, performance and usability have become increasingly important. The evaluation must be based on a larger set of reference data, and workflow integration must be achieved before CBIR-CAD is really established in clinical practice. Bentham Open 2011-07-27 /pmc/articles/PMC3149811/ /pubmed/21892374 http://dx.doi.org/10.2174/1874431101105010058 Text en © Depeursinge et al.; Licensee Bentham Open. http://creativecommons.org/licenses/by-nc/3.0/ This is an open access article licensed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/) which permits unrestricted, non-commercial use, distribution and reproduction in any medium, provided the work is properly cited. |
spellingShingle | Article Depeursinge, Adrien Fischer, Benedikt Müller, Henning Deserno, Thomas M Prototypes for Content-Based Image Retrieval in Clinical Practice |
title | Prototypes for Content-Based Image Retrieval in Clinical Practice |
title_full | Prototypes for Content-Based Image Retrieval in Clinical Practice |
title_fullStr | Prototypes for Content-Based Image Retrieval in Clinical Practice |
title_full_unstemmed | Prototypes for Content-Based Image Retrieval in Clinical Practice |
title_short | Prototypes for Content-Based Image Retrieval in Clinical Practice |
title_sort | prototypes for content-based image retrieval in clinical practice |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3149811/ https://www.ncbi.nlm.nih.gov/pubmed/21892374 http://dx.doi.org/10.2174/1874431101105010058 |
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