Digital image processing (2nd ed.)
Digital image processing (2nd ed.)
The Science of Fractal Images
Fast Chain Coding of Region Boundaries
IEEE Transactions on Pattern Analysis and Machine Intelligence
Statistical Pattern Recognition: A Review
IEEE Transactions on Pattern Analysis and Machine Intelligence
Feature extraction using wavelet and fractal
Pattern Recognition Letters
Pattern Recognition, Third Edition
Pattern Recognition, Third Edition
Computational Characterization of Thyroid Tissue in the Radon Domain
CBMS '07 Proceedings of the Twentieth IEEE International Symposium on Computer-Based Medical Systems
IEEE Transactions on Computers
An efficient chain code with Huffman coding
Pattern Recognition
IEEE Transactions on Information Technology in Biomedicine
Hi-index | 0.00 |
In this paper, a novel computer-based approach is proposed for malignancy risk assessment of thyroid nodules in ultrasound images. The proposed approach is based on boundary features and is motivated by the correlation which has been addressed in medical literature between nodule boundary irregularity and malignancy risk. In addition, local echogenicity variance is utilized so as to incorporate information associated with local echogenicity distribution within nodule boundary neighborhood. Such information is valuable for the discrimination of high-risk nodules with blurred boundaries from medium-risk nodules with regular boundaries. Analysis of variance is performed, indicating that each boundary feature under study provides statistically significant information for the discrimination of thyroid nodules in ultrasound images, in terms of malignancy risk. k-nearest neighbor and support vector machine classifiers are employed for the classification tasks, utilizing feature vectors derived from all combinations of features under study. The classification results are evaluated with the use of the receiver operating characteristic. It is derived that the proposed approach is capable of discriminating between medium-risk and high-risk nodules, obtaining an area under curve, which reaches 0.95.