Abstract

The objective of this paper is to provide a complete solution to estimate the volume of the thyroid gland directly from US images. In this paper, the radial basis function (RBF) neural network is used to classify blocks of the thyroid gland; the integral region is further acquired by applying a specific region growing method to potential points. The parameters for evaluating the thyroid volume is estimated by a particle swarm optimization (PSO) algorithm. Experimental results of the thyroid region segmentation and volume estimation in US images show high potential of our proposed approach.

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