Abstract:In this paper, steady state temperature variations in the human brain due to different electrical and physical changes have been studied considering different thermal ablation treatment requirements using RF probe. Initially, a subject specific voxel-based electrical model has been constructed from Digital Imaging and Communication in Medicine (DICOM) formatted Computed Tomography (CT) or Magnetic Resonance (MR) based image stacks with different pixel characteristics using the Hounsfield unit extraction techni… Show more
In order to establish a treatment plan to predict therapeutic parameters accurately by radio frequency ablation (RFA) in spinal tumor, we use finite element method (FEM) to build a database in different therapeutic parameters (voltages 10–30[Formula: see text]V and heating-up time 120–1200[Formula: see text]s) and structures of electrode (single and multi). For predicting parameters through database, we compare three modes. We acquired 383 sets of data as database. The results show support vector machine (SVM) model is the best one to be applied in treatment planning, in which error rates (0 and 0.33%) were the smallest and correlation coefficients (1.000 and 0.999) were the closest to 1.
In order to establish a treatment plan to predict therapeutic parameters accurately by radio frequency ablation (RFA) in spinal tumor, we use finite element method (FEM) to build a database in different therapeutic parameters (voltages 10–30[Formula: see text]V and heating-up time 120–1200[Formula: see text]s) and structures of electrode (single and multi). For predicting parameters through database, we compare three modes. We acquired 383 sets of data as database. The results show support vector machine (SVM) model is the best one to be applied in treatment planning, in which error rates (0 and 0.33%) were the smallest and correlation coefficients (1.000 and 0.999) were the closest to 1.
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