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Spatial statistics based feature descriptor for RF ultrasound data
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- Klein, T. (author)
- Computer Aided Medical Procedures (CAMP), Technische Universität München, Germany
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- Hansson, M. (author)
- Malmö högskola,Teknik och samhälle (TS)
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- Navab, N. (author)
- Computer Aided Medical Procedures (CAMP), Technische Universität München, Germany
- (creator_code:org_t)
- Institute of Electrical and Electronics Engineers (IEEE), 2011
- 2011
- English.
- In: 2011 IEEE International Symposium on Biomedical Imaging: From Nano to Macro. - : Institute of Electrical and Electronics Engineers (IEEE). - 9781424441273
- Conference paper (peer-reviewed)
Abstract
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- In this paper we present a feature descriptor, based on a Markov random field (MRF) texture model, for radio-frequency (RF) ultrasound data. The proposed approach combines global data statistics in terms of a maximum-likelihood-estimated (MLE) distribution with local pattern characteristics employing MRF interaction parameters. This combining approach facilitates the encoding of the underlying nature of the ultrasound envelope data and therefore represents a powerful feature descriptor. Applicability and performance is showcased on RF data from a human neck.
Subject headings
- TEKNIK OCH TEKNOLOGIER -- Medicinteknik (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Medical Engineering (hsv//eng)
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