Automatic multilevel medical image annotation and retrieval
Document Type
Article
Publication Date
1-1-2008
Abstract
Image retrieval at the semantic level mostly depends on image annotation or image classification. Image annotation performance largely depends on three issues: (1) automatic image feature extraction; (2) a semantic image concept modeling; (3) algorithm for semantic image annotation. To address first issue, multilevel features are extracted to construct the feature vector, which represents the contents of the image. To address second issue, domain-dependent concept hierarchy is constructed for interpretation of image semantic concepts. To address third issue, automatic multilevel code generation is proposed for image classification and multilevel image annotation. We make use of the existing image annotation to address second and third issues. Our experiments on a specific domain of X-ray images have given encouraging results.
Keywords
image classification image annotation image processing machine learning face detection classification
Divisions
ai
Publication Title
Journal of Digital Imaging
Volume
21
Issue
3
Additional Information
ISI Document Delivery No.: 338TP Times Cited: 4 Cited Reference Count: 15 Mueen, A. Zainuddin, R. Baba, M. Sapiyan Springer New york