Signal detection using support vector machines in the presence of ultrasonic speckle

Constantine L. Kotropoulos; Ioannis Pitas

doi:10.1117/12.462166

11 April 2002 Signal detection using support vector machines in the presence of ultrasonic speckle

Constantine L. Kotropoulos, Ioannis Pitas

Proceedings Volume 4687, Medical Imaging 2002: Ultrasonic Imaging and Signal Processing; (2002) https://doi.org/10.1117/12.462166
Event: Medical Imaging 2002, 2002, San Diego, California, United States

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.

Citation Download Citation

Constantine L. Kotropoulos and Ioannis Pitas "Signal detection using support vector machines in the presence of ultrasonic speckle", Proc. SPIE 4687, Medical Imaging 2002: Ultrasonic Imaging and Signal Processing, (11 April 2002); https://doi.org/10.1117/12.462166

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