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Authors
Advisor(s)
Abstract(s)
Safety and efficiency of thermal therapies strongly rely on the ability to quantify
temperature evolution in the treatment region. Research has been developed in this
field, and both invasive and non-invasive technologies have been reported. Till now,
only the magnetic resonance imaging (MRI) achieved the hyperthermia/diathermia
gold standard value of temperature resolution of 0.5oC in 1cm3, in an in-vivo scenario.
However, besides the cost of MRI technology, it does not enable a broad-range
therapy application due to its complex environment. Alternatively, backscattered
ultrasound (BSU) seems a promising tool for thermal therapy, but till now its performance
was only quantitatively tested on homogeneous media and on single-intensity
and three-point assessment have been reported.
This thesis reports the research performed on the evaluation of time-spatialtemperature
evolution based mainly on BSU signals within artificial tissues. Extensive
operating conditions were tested on several experimental setups based on
dedicated phantoms. Four and eight clinical ultrasound intensities, up to five spatial
points, homogeneous and heterogeneous multi-layered phantoms were considered.
Spectral and temporal temperature-dependent BSU features were extracted,
and applied as invasive and non-invasive methodologies input information. Softcomputing
methodologies have been used for temperature estimation. From linear
iterative model structure models, to multi-objective genetic algorithms (MOGA)
model structure optimisation for linear models, radial basis functions neural netxi
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works (RBFNNs), RBFNNs with linear inputs (RBFLICs), and for the adaptivenetwork-
based fuzzy inference system (ANFIS) have been used to estimate the temperature
induced on the phantoms. The MOGA+RBFNN methodology, fed with
completely data-driven information, estimated temperature with maximum absolute
errors less than 0.5oC within two spatial axes.
The proposed MOGA+RBFNN methodology applied to non-invasive estimation
on multi-layered media, is a innovative approach, as far as known, and enabled
a step forward on the therapeutic temperature characterisation, motivating future
instrumentation temperature control.
Description
Tese dout., Engenharia electrónica e computação - Processamento de sinal, Universidade do Algarve, 2008
Keywords
Teses Processamento de sianl Redes neuronais Algoritmos genéticos Terapias Temperatura