Temperature models of a homogeneous medium under therapeutic ultrasound

Teixeira, C. A.; Cortela, G.; Gomez, H.; Ruano, M. Graça; Ruano, Antonio; Negreira, C.; Pereira, W. C. A.

http://hdl.handle.net/10400.1/2295

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Abstract(s)

Temperature modelling of human tissue subjected to ultrasound for therapeutic use is essential for an accurate instrumental assessment and calibration. Prior studies developed on a homogeneous medium are hereby reported. Non-linear punctual temperature modelling is proposed by means of Radial Basis Functions Neural Network (RBFNN) structures. The best-performed structures are obtained using a Multiobjective Genetic Algorithm (MOGA). The best performed neural structure presents a Root Mean Square Error (RMSE) of one order magnitude less than the one presented by the best behaved linear model - the AutoRegressive with eXogenous inputs (ARX); The maximum absolute error achieved with the neural model was 0.2 ºC.

Keywords

Temperature modelling Neural networks Multi-objective genetic algorithms Ultrasound

URI

http://hdl.handle.net/10400.1/2295

Citation

Teixeira, C. A.; Cortela, G.; Gomez, H.; Ruano, M. G.; Ruano, A. E.; Negreira, C.; Pereira, W. C. A. Temperature models of a homogeneous medium under therapeutic ultrasound, Revista Brasileira de Engenharia Biomédica, 20, 2-3, 97-101, 2004.