Introduction to statistical pattern recognition (2nd ed.)
Introduction to statistical pattern recognition (2nd ed.)
Texture Feature Coding Method for Classification of Liver Sonography
ECCV '96 Proceedings of the 4th European Conference on Computer Vision-Volume I - Volume I
Architecture of Systems Problem Solving
Architecture of Systems Problem Solving
Different types of image texture features in ultrasound of patients with lymphocytic thyroiditis
ISICT '03 Proceedings of the 1st international symposium on Information and communication technologies
WISICT '04 Proceedings of the winter international synposium on Information and communication technologies
ACST'07 Proceedings of the third conference on IASTED International Conference: Advances in Computer Science and Technology
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The success of discrimination between normal and inflamed parenchyma of thyroid gland by means of automatic texture analysis is largely determined by selecting descriptive yet simple and independent sonographic image features. We replace the standard non-systematic process of feature selection by systematic feature construction based on the search for the separation distances among a clique of n pixels that minimise conditional entropy of class label given all data. The procedure is fairly general and does not require any assumptions about the form of the class probability density function. We show that a network of weak Bayes classifiers using 4-cliques as features and combined by majority vote achieves diagnosis recognition accuracy of 92%, as evaluated on a set of 741 B-mode sonographic images from 39 subjects. The results suggest the possibility to use this method in clinical diagnostic process.