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Chair for Computer Aided Medical Procedures & Augmented Reality
Lehrstuhl für Informatikanwendungen in der Medizin & Augmented Reality

T. Klein, M. Hansson, N. Navab
Spatial Statistics Based Feature Descriptor for RF Ultrasound Data
IEEE International Symposium on Biomedical Imaging: From Nano to Macro (ISBI 2011), Chicago, Illinois, USA, March 30 - April 2, 2011 (bib)

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.
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