Authors:
Peijiang Yuan
;
Bo Zhang
and
Jianmin Li
Affiliation:
Tsinghua University, China
Keyword(s):
Content-Based Medical Video Retrieval (CBMVR), Artificial Potential Field (APF), Multimodal Information Retrieval.
Related
Ontology
Subjects/Areas/Topics:
Applications
;
Applications and Services
;
Computer Vision, Visualization and Computer Graphics
;
Image Enhancement and Restoration
;
Image Formation and Preprocessing
;
Imaging in Computing and Business (Document Imaging, Metadata, Quality Control)
;
Medical Imaging
;
Pattern Recognition
;
Software Engineering
Abstract:
Image based medical diagnosis plays an important role in improving the quality of health-care industry. Content based image retrieval (CBIR) has been successfully implemented in medical fields to help physicians in training and surgery. Many radiological and pathological images and videos are generated by hospitals, universities and medical centers with sophisticated image acquisition devices. Images and Videos that help senior or junior physician to practice medical surgery become more and more popular and easier to access through different ways. To help learn the process of a surgery or even make decisions is one of the main objectives of the content based image and video retrieval system. In this paper, a contented-based multimodal medical video retrieval system (CBMVR) for medical image and video databases is addressed. Some key issues are discussed. A new feature representation method named Artificial Potential Field (APF) is addressed which is specially useful in symmetrical im
aging feature extraction. Experimental results show that, with this CBMVR, both the senior and junior physicians can benefit from the mass data of medical images and videos.
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