Thyroid segmentation and volume estimation in ultrasound images

Author

Chang, Chuan-Yu ; Lei, Yue-Fong ; Tseng, Chin-Hsiao ; Shih, Shyang-Rong

Author_Institution

Dept. of Comput. & Commun. Eng., Nat. Yunlin Univ. of Sci. & Technol., Yunlin

fYear

2008

fDate

12-15 Oct. 2008

Firstpage

3442

Lastpage

3447

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.

Keywords

biological organs; biomedical ultrasonics; image classification; image segmentation; medical image processing; particle swarm optimisation; radial basis function networks; PSO algorithm; RBF neural network; US image classification; particle swarm optimization; radial basis function; region growing method; thyroid gland segmentation; ultrasound images; volume estimation; Biochemistry; Computed tomography; Endocrine system; Fluids and secretions; Glands; Hospitals; Image segmentation; Neural networks; Particle swarm optimization; Ultrasonic imaging; Neural network; Particle swarm optimization; Radial basis function; Region growing; Thyroid segmentation;

fLanguage

English

Publisher

ieee

Conference_Titel

Systems, Man and Cybernetics, 2008. SMC 2008. IEEE International Conference on

Conference_Location

Singapore

ISSN

1062-922X

Print_ISBN

978-1-4244-2383-5

Electronic_ISBN

1062-922X

Type

conf

DOI

10.1109/ICSMC.2008.4811830

Filename

4811830