Content-based retrieval of medical images : landmarking, indexing, and relevance feedback /
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| Corporate Author: | |
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| Format: | eBook |
| Language: | English |
| Published: |
[San Rafael, Calif.] :
Morgan & Claypool,
[2013]
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| Series: | Synthesis lectures on biomedical engineering ;
#48. |
| Subjects: |
Anisotropic diffusion
> Breast cancer
> Breast density
> Computer-aided diagnosis
> Contentbased image retrieval
> Fibroglandular disk
> Granulometry
> Image enhancement
> Image segmentation
> Information retrieval
> Kohonen self-organizing map
> Landmarking of images
> Mammography
> Nipple detection
> Pattern recognition
> Pectoral muscle
> Picture archival and communication system
> Radon transform
> Relevance feedback
> Texture analysis
> Wiener filter
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| Online Access: | Connect to the full text of this electronic book Connect to the full text of this electronic book |
| Abstract: | Content-based image retrieval (CBIR) is the process of retrieval of images from a database that are similar to a query image, using measures derived from the images themselves, rather than relying on accompanying text or annotation. To achieve CBIR, the contents of the images need to be characterized by quantitative features; the features of the query image are compared with the features of each image in the database and images having high similarity with respect to the query image are retrieved and displayed. CBIR of medical images is a useful tool and could provide radiologists with assistance in the form of a display of relevant past cases. One of the challenging aspects of CBIR is to extract features from the images to represent their visual, diagnostic, or application-specific information content. In this book, methods are presented for preprocessing, segmentation, landmarking, feature extraction, and indexing of mammograms for CBIR. The preprocessing steps include anisotropic diffusion and the Wiener filter to remove noise and perform image enhancement. Techniques are described for segmentation of the breast and fibroglandular disk, including maximum entropy, a moment-preserving method, and Otsu's method. Image processing techniques are described for automatic detection of the nipple and the edge of the pectoral muscle via analysis in the Radon domain. By using the nipple and the pectoral muscle as landmarks, mammograms are divided into their internal, external, upper, and lower parts for further analysis. Methods are presented for feature extraction using texture analysis, shape analysis, granulometric analysis, moments, and statistical measures. |
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| Item Description: | Part of: Synthesis digital library of engineering and computer science. "The aim of this book is to present some of the recent developments in the areas of CBIR [content-based image retrieval] and CAD [computer-aided diagnosis], with particular reference to mammography and breast cancer"--Pref. Electronic resource. |
| Physical Description: | 1 online resource (xxiv, 119 pages) : illustrations (some color), portraits |
| Bibliography: | Includes bibliographical references (pages 101-113) and index. |
| ISBN: | 9781627051422 (electronic bk.) 1627051422 (electronic bk.) |
| ISSN: | 1930-0336 ; |