Off-campus South Dakota State University users: To download campus access theses, please use the following link to log into our proxy server with your South Dakota State University ID and password.
Non-South Dakota State University users: Please talk to your librarian about requesting this thesis through interlibrary loan.
Thesis - University Access Only
Master of Science (MS)
Electrical Engineering and Computer Science
Sung Y. Shin
As Computer Aided Diagnosis (CAD) is being a regular routine in the medical field, processing distinctive features from the image aid physicians’ decisions. In case of breast cancer, beside from determining whether the tumor is benign or malignant, similar cases found in different patients provide medical doctors viral information before one’s final decision. Thus, detecting similar tumor cases can provide decisive information to the doctors. In this paper, shape based image retrieval method using arc difference ratio (ADR) has been introduced and compared with different shape based image retrieval systems using different shape features such as Contour to Centroid Triangulation (CTCT) method, and Sectored Contour to Centroid Triangulation (SCTCT) method. All image retrieval systems have been tested with 1,300 binary object images that have been through feature extraction using Support Vector Machine from actual breast mammograms. In order to inspect the matching rate of shape based image retrieval system, each system results were compared with sectored object matching method. 20 test sets were experimented and proposed shape based image retrieval system using ADR shows the highest matching rate compared to others.
Library of Congress Subject Headings
Breast -- Imaging
Breast -- Cancer -- Diagnosis
Diagnostic imaging -- Digital techniques
Includes bibliographical references (pages 28-31)
Number of Pages
South Dakota State University
In Copyright - Non-Commercial Use Permitted
Jung, ByungKwan, "Shape Based Breast Medical Image Retrieval System using Arc Difference Rate" (2014). Electronic Theses and Dissertations. 2012.