Active Contours Guided by Echogenicity and Texture for Delineation of Thyroid Nodules in Ultrasound Images
IEEE Transactions on Information Technology in Biomedicine
Thyroid nodules are solid or cystic lumps formed in the thyroid gland and may be caused by a variety of thyroid disorders. This paper presents a novel active contour model for precise delineation of thyroid nodules of various shapes according to their echogenicity and texture, as displayed in ultrasound (US) images. The proposed model, named JET (Joint Echogenicity-Texture), is based on a modified Mumford-Shah functional that, in addition to regional image intensity, incorporates statistical
... ture information encoded by feature distributions. The distributions are aggregated within the functional through new log-likelihood goodness-of-fit terms. The JET model requires only a rough region of interest within the thyroid gland as input and automatically proceeds with precise delineation of the nodules, revealing their shape and size. The performance of the JET model was validated on a range of US images displaying hypoechoic and isoechoic nodules of various shapes. The quantification of the results shows that the JET model: 1) provides precise delineations of thyroid nodules as compared to "ground truth" delineations obtained by experts, and 2) copes with the limitations of the previous thyroid US delineation approaches as it is capable of d elineating thyroid nodules regardless of their echogenicity or shape. He has been working for over ten years in the field of medical informatics and has been collaborating with many European hospitals and health centers as an expert on biomedical systems. Currently, among other academic positions, he holds a senior researcher position at the University of Athens, Greece. Dr. Iakovidis has co-authored more than 60 research papers and book chapters, and he is a reviewer in 12 international journals, including IEEE Trans. on Image Processing, and IEEE Trans. Biomedical Engineering. He has been actively involved in more than 10 European and National R&D projects. His research interests include image processing and analysis, data mining, pattern recognition with applications on biomedical systems and bioinformatics.