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Automated Detection of Healthy and Diseased Aortae from Images Obtained by Contrast-Enhanced CT Scan
Joint Authors
Arisawa, Hiroshi
Gayhart, Michael
Source
Computational and Mathematical Methods in Medicine
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-7, 7 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-03-31
Country of Publication
Egypt
No. of Pages
7
Main Subjects
Abstract EN
Purpose.
We developed the next stage of our computer assisted diagnosis (CAD) system to aid radiologists in evaluating CT images for aortic disease by removing innocuous images and highlighting signs of aortic disease.
Materials and Methods.
Segmented data of patient’s contrast-enhanced CT scan was analyzed for aortic dissection and penetrating aortic ulcer (PAU).
Aortic dissection was detected by checking for an abnormal shape of the aorta using edge oriented methods.
PAU was recognized through abnormally high intensities with interest point operators.
Results.
The aortic dissection detection process had a sensitivity of 0.8218 and a specificity of 0.9907.
The PAU detection process scored a sensitivity of 0.7587 and a specificity of 0.9700.
Conclusion.
The aortic dissection detection process and the PAU detection process were successful in removing innocuous images, but additional methods are necessary for improving recognition of images with aortic disease.
American Psychological Association (APA)
Gayhart, Michael& Arisawa, Hiroshi. 2013. Automated Detection of Healthy and Diseased Aortae from Images Obtained by Contrast-Enhanced CT Scan. Computational and Mathematical Methods in Medicine،Vol. 2013, no. 2013, pp.1-7.
https://search.emarefa.net/detail/BIM-447005
Modern Language Association (MLA)
Gayhart, Michael& Arisawa, Hiroshi. Automated Detection of Healthy and Diseased Aortae from Images Obtained by Contrast-Enhanced CT Scan. Computational and Mathematical Methods in Medicine No. 2013 (2013), pp.1-7.
https://search.emarefa.net/detail/BIM-447005
American Medical Association (AMA)
Gayhart, Michael& Arisawa, Hiroshi. Automated Detection of Healthy and Diseased Aortae from Images Obtained by Contrast-Enhanced CT Scan. Computational and Mathematical Methods in Medicine. 2013. Vol. 2013, no. 2013, pp.1-7.
https://search.emarefa.net/detail/BIM-447005
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-447005