Evaluation of a content-based retrieval system for blood cell images with automated methods
Document Type
Article
Publication Date
1-1-2011
Abstract
Content-based image retrieval techniques have been extensively studied for the past few years. With the growth of digital medical image databases, the demand for content-based analysis and retrieval tools has been increasing remarkably. Blood cell image is a key diagnostic tool for hematologists. An automated system that can retrieved relevant blood cell images correctly and efficiently would save the effort and time of hematologists. The purpose of this work is to develop such a content-based image retrieval system. Global color histogram and wavelet-based methods are used in the prototype. The system allows users to search by providing a query image and select one of four implemented methods. The obtained results demonstrate the proposed extended query refinement has the potential to capture a user's high level query and perception subjectivity by dynamically giving better query combinations. Color-based methods performed better than wavelet-based methods with regard to precision, recall rate and retrieval time. Shape and density of blood cells are suggested as measurements for future improvement. The system developed is useful for undergraduate education.
Keywords
Blood Cell Images, Automated methods
Divisions
fsktm
Publication Title
Journal of Medical Systems
Volume
35
Issue
4
Publisher
Springer Verlag
Additional Information
Computer Science & Information Technology Faculty, University of Malaya, Kuala Lumpur, Malaysia,