Title :
Estimating a parametric model of temperature distribution from an ultrasound image sequence during HIFU therapy
Author :
Ye, Guoliang ; Noble, J. Alison ; Smith, Penny Probert
Author_Institution :
Dept. of Eng. Sci., Oxford Univ.
Abstract :
This paper presents a novel method to estimate a parametric model of temperature distribution from a high-intensity focused ultrasound sequence using a Kalman filter approach. The Kaiman filter enables an initial temperature map, derived from (say) the echo-strain method, to not only be smoothed along the heat conduction direction, but to adopt a shape similar to the defined parametric shape of a sensor model. Effects of the model parameters and the covariances of the Kalman filter are investigated. Experimental results on phantom data show that the overall quality of the resulting temperature map is improved using our approach, enabling the extent of tissue "damage" caused by heating to be readily estimated through a visual display
Keywords :
Kalman filters; biological tissues; biomedical ultrasonics; biothermics; covariance analysis; heat conduction; image sequences; medical image processing; phantoms; radiation therapy; smoothing methods; HIFU therapy; Kalman filter; covariances; echo-strain method; heat conduction; high-intensity focused ultrasound; initial temperature map; parametric model; phantom; smoothing method; temperature distribution; tissue damage; ultrasound image sequence; Filters; Focusing; Image sequences; Medical treatment; Parametric statistics; Shape; Temperature distribution; Temperature sensors; Thermal sensors; Ultrasonic imaging;
Conference_Titel :
Biomedical Imaging: Nano to Macro, 2006. 3rd IEEE International Symposium on
Conference_Location :
Arlington, VA
Print_ISBN :
0-7803-9576-X
DOI :
10.1109/ISBI.2006.1625061
