Active contours guided by echogenicity and texture for delineation of thyroid nodules in ultrasound images

Authors:
Michalis A. Savelonas;Dimitris K. Iakovidis;Ioannis Legakis;Dimitris Maroulis
Affiliations:
Department of Informatics and Telecommunications, University of Athens, Athens, Greece;Department of Informatics and Telecommunications, University of Athens, Athens, Greece;Department of Endocrinology, Henry Dunant Hospital and University of Athens, Athens, Greece;Department of Informatics and Telecommunications, University of Athens, Athens, Greece
Venue:
IEEE Transactions on Information Technology in Biomedicine - Special section on biomedical informatics
Year:
2009

Citing 11
Cited 0

Fronts propagating with curvature-dependent speed: algorithms based on Hamilton-Jacobi formulations

Journal of Computational Physics
Multiresolution Gray-Scale and Rotation Invariant Texture Classification with Local Binary Patterns

IEEE Transactions on Pattern Analysis and Machine Intelligence
Texture Features in the Classification of Melanocytic Lesions

ICIAP '97 Proceedings of the 9th International Conference on Image Analysis and Processing-Volume II
Segmentation of Meningiomas and Low Grade Gliomas in MRI

MICCAI '99 Proceedings of the Second International Conference on Medical Image Computing and Computer-Assisted Intervention
Pattern Recognition, Third Edition

Pattern Recognition, Third Edition
A hybrid multi-scale model for thyroid nodule boundary detection on ultrasound images

Computer Methods and Programs in Biomedicine
A genetically optimized level set approach to segmentation of thyroid ultrasound images

Applied Intelligence
3-D snake for US in margin evaluation for malignant breast tumor excision using mammotome

IEEE Transactions on Information Technology in Biomedicine
An automated method for lumen and media-adventitia border detection in a sequence of IVUS frames

IEEE Transactions on Information Technology in Biomedicine
Variable Background Active Contour Model for Computer-Aided Delineation of Nodules in Thyroid Ultrasound Images

IEEE Transactions on Information Technology in Biomedicine
Active contours without edges

IEEE Transactions on Image Processing

Quantified Score

Hi-index	0.00

Visualization

Abstract

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 joint echogenicity-texture (JET), is based on a modifiedMumford-Shah functional that, in addition to regional image intensity, incorporates statistical texture 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 delineating thyroid nodules regardless of their echogenicity or shape.