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.
This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each authors copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.

Edit | Attach | Refresh | Diffs | More | Revision r1.11 - 19 Jul 2016 - 16:26 - NassirNavab

Lehrstuhl für Computer Aided Medical Procedures & Augmented Reality    rss.gif