Currently, the safety assessment of radio-frequency (RF) heating in computational modeling is limited by the available numerical models which are not patient-specific although RF-induced heating depends on the physical characteristics of the patient. The numerical model generation is difficult due to the highly time-consuming segmentation process. Therefore, having fewer types of segmented structures simplifies the generation of numerical models. In this study, we used the k-means clustering method to reduce the number of dielectric properties of an existing numerical model and investigated the resulting difference in SAR with respect to the number of clusters.
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