A genetically optimized level set approach to segmentation of thyroid ultrasound images

This paper presents a novel framework for thyroid ultrasound image segmentation that aims to accurately delineate thyroid nodules. This framework, named GA-VBAC incorporates a level set approach named Variable Background Active Contour model (VBAC) that utilizes variable background regions, to reduce the effects of the intensity inhomogeneity in the thyroid ultrasound images. Moreover, a parameter tuning mechanism based on Genetic Algorithms (GA) has been considered to search for the optimal VBAC parameters automatically, without requiring technical skills. Experiments were conducted over a range of ultrasound images displaying thyroid nodules. The results show that the proposed GA-VBAC framework provides an efficient, effective and highly objective system for the delineation of thyroid nodules.

• Type: Journal
• Year: 2007
• Where: APIN
• Authors: Dimitrios K. Iakovidis, Michalis A. Savelonas, Stavros A. Karkanis, Dimitrios E. Maroulis
• Keywords: APIN 2007, Thyroid Nodules, Thyroid Ultrasound Images, Variable Background