A desirable content-based image retrieval (CBIR) system would classify extracted image features to support some form of semantic retrieval. The Lister Hill National Center for Biomedical Communications, an intramural R&D division of the National Library for Medicine (NLM), maintains an archive of digitized X-rays of the cervical and lumbar spine taken as part of the second national health and nutrition examination survey (NHANES II). It is our goal to provide shape-based access to digitized X-rays including retrieval on automatically detected and classified pathology, e.g., anterior osteophytes. This is done using radius of curvature analysis along the anterior portion, and morphological analysis for quantifying protrusion regions along the vertebra boundary. Experimental results are presented for the classification of 704 cervical spine vertebrae by evaluating the features using a multi-layer perceptron (MLP) based approach. In this paper, we describe the design and current status of the content-based image retrieval (CBIR) system and the role of neural networks in the design of an effective multimedia information retrieval system.
S. Antani et al., "Vertebra Shape Classification using MLP for Content-Based Image Retrieval," Proceedings of the International Joint Conference on Neural Networks, 2003, Institute of Electrical and Electronics Engineers (IEEE), Jan 2003.
The definitive version is available at http://dx.doi.org/10.1109/IJCNN.2003.1223324
International Joint Conference on Neural Networks, 2003
Electrical and Computer Engineering
Keywords and Phrases
704 Cervical Spine Vertebrae; Lister Hill National Center for Biomedical Communications; MLP; National Library for Medicine; Anterior Osteophytes; Anterior Portion; Automatically Classified Pathology; Automatically Detected Pathology; Bone; Cervical Digitized X-Ray; Content-Based Image Retrieval; Content-Based Retrieval; Curvature Analysis; Diagnostic Radiography; Image Classification; Image Features Extraction; Image Retrieval; Information Retrieval Systems; Lumbar Spine Digitized X-Ray; Medical Image Processing; Morphological Analysis; Multilayer Perceptron; Multilayer Perceptrons; Multimedia Information Retrieval System; Neural Networks; Protrusion Regions Quantification; Second National Health and Nutrition Examination Survey; Semantic Retrieval; Vertebra Boundary; Vertebra Shape Classification
International Standard Serial Number (ISSN)
Article - Conference proceedings
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