Utilize este identificador para referenciar este registo: http://hdl.handle.net/10400.1/2242
Título: Noninvasive black-box temperature simulation: precise spatial generalisation
Autor: Teixeira, C. A.
Ruano, A. E.
Ruano, M. Graça
Pereira, W. C. A.
Palavras-chave: Non-invasive temperature estimation
Black-box models
Rradial basis functions neural networks
Multi-objective genetic algorithms
Data: 2006
Citação: Teixeira, C. A.; Ruano, A. E.; Ruano, M. G.; Pereira, W. C. A. Noninvasive black-box temperature simulation: precise spatial generalisation, Trabalho apresentado em XX Brasilian Congress on Biomedical Engineering-XX CBEB, In Proceedings of the XX Brasilian Congress on Biomedical Engineering-XX CBEB, São Paulo, 2006.
Resumo: In this paper the performance of a blackbox methodology is accessed for non-invasive timespatial temperature estimation. A gel-based phantom was heated at different intensities with therapeutic ultrasound, while temperature and RF-lines were collected. The models were trained and its structure selected to estimate the temperature in three discrete points, and at the end validated in unseen data, in the trained points and in two additional intermediate untrained points, in order to test the model s spatial generalization capacity. The best model had low complexity and a high generalization capacity, presenting in both the points and intensities a maximum absolute error inferior to 0.5 ºC, as desired in hyperthermia/diathermia.
Peer review: yes
URI: http://hdl.handle.net/10400.1/2242
Aparece nas colecções:FCT2-Artigos (em revistas ou actas indexadas)

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