We develop a multilayer perceptron focused ultrasound temperature network (Fust-Net), which combines patient demographic characteristics, head indicators and treatment parameters to predict the treatment temperature of MRgFUS. The magnitude of the effect of 6 different predictors or combinations of predictors on the efficacy of Fust-Net for target temperature prediction was analyzed and tested. The contributions of each factor in the Fust-Net with best performance were calculated. Set1: Duration; Set2: Duration+Energy; Set3: Duration+Energy+SDR; Set4: Duration+Energy+SDR+Size; Set5: Duration+Energy+SDR+Size+Area; Set6: Duration+Energy+SDR+Size+Area+Course.
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