The nature of statistical learning theory
The nature of statistical learning theory
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
Computer-Aided Thyroid Nodule Detection in Ultrasound Images
CBMS '05 Proceedings of the 18th IEEE Symposium on Computer-Based Medical Systems
Neural Networks for Applied Sciences and Engineering
Neural Networks for Applied Sciences and Engineering
Computational Characterization of Thyroid Tissue in the Radon Domain
CBMS '07 Proceedings of the Twentieth IEEE International Symposium on Computer-Based Medical Systems
Fuzzy Local Binary Patterns for Ultrasound Texture Characterization
ICIAR '08 Proceedings of the 5th international conference on Image Analysis and Recognition
Pattern Recognition, Fourth Edition
Pattern Recognition, Fourth Edition
IEEE Transactions on Information Technology in Biomedicine
Support vector machines for histogram-based image classification
IEEE Transactions on Neural Networks
Efficient and effective ultrasound image analysis scheme for thyroid nodule detection
ICIAR'07 Proceedings of the 4th international conference on Image Analysis and Recognition
Hi-index | 0.00 |
In this paper, we present a computer-aided-diagnosis (CAD) system prototype, named TND (Thyroid Nodule Detector), for the detection of nodular tissue in ultrasound (US) thyroid images and videos acquired during thyroid US examinations. The proposed system incorporates an original methodology that involves a novel algorithm for automatic definition of the boundaries of the thyroid gland, and a novel approach for the extraction of noise resilient image features effectively representing the textural and the echogenic properties of the thyroid tissue. Through extensive experimental evaluation on real thyroid US data, its accuracy in thyroid nodule detection has been estimated to exceed 95%. These results attest to the feasibility of the clinical application of TND, for the provision of a second more objective opinion to the radiologists by exploiting image evidences.