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Proceedings Paper

Signal detection using support vector machines in the presence of ultrasonic speckle
Author(s): Constantine L. Kotropoulos; Ioannis Pitas
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Paper Abstract

Support Vector Machines are a general algorithm based on guaranteed risk bounds of statistical learning theory. They have found numerous applications, such as in classification of brain PET images, optical character recognition, object detection, face verification, text categorization and so on. In this paper we propose the use of support vector machines to segment lesions in ultrasound images and we assess thoroughly their lesion detection ability. We demonstrate that trained support vector machines with a Radial Basis Function kernel segment satisfactorily (unseen) ultrasound B-mode images as well as clinical ultrasonic images.

Paper Details

Date Published: 11 April 2002
PDF: 12 pages
Proc. SPIE 4687, Medical Imaging 2002: Ultrasonic Imaging and Signal Processing, (11 April 2002); doi: 10.1117/12.462166
Show Author Affiliations
Constantine L. Kotropoulos, Aristotle Univ. of Thessaloniki (Greece)
Ioannis Pitas, Aristotle Univ. of Thessaloniki (Greece)

Published in SPIE Proceedings Vol. 4687:
Medical Imaging 2002: Ultrasonic Imaging and Signal Processing
Michael F. Insana; William F. Walker, Editor(s)

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