THE USE OF HELLWIG’S METHOD FOR DIMENSION REDUCTION IN FEATURE SPACE OF THYROID ULTRASOUND IMAGES
Zbigniew Omiotek
zomiotek@gmail.comLublin University of Technology, Faculty of Electrical Engineering and Computer Science (Poland)
Waldemar Wójcik
Lublin University of Technology, Faculty of Electrical Engineering and Computer Science (Poland)
Abstract
This paper presents the use of Hellwig’s method for dimension reduction in feature space of thyroid ultrasound images. On the base of this method, the combination of three features with the greatest value of Hellwig’s index information capacity from the input set of 283 features was obtained. This set was used to build and test the classifiers. Classification results were compared with the results obtained for a set of 48 features obtained using correlation method. It turned out that the accuracy of classifiers built on the base of 3 features is not worse than the accuracy of classifiers built on the base of 48 features, and in some cases it is even higher. This suggests that the Hellwig’s method can be used as an effective method for dimension reduction in feature space for the future thyroid ultrasound images classification.
Keywords:
Hellwig’s method, Hashimoto’s disease, image processing, texture classificationReferences
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Authors
Zbigniew Omiotekzomiotek@gmail.com
Lublin University of Technology, Faculty of Electrical Engineering and Computer Science Poland
Authors
Waldemar WójcikLublin University of Technology, Faculty of Electrical Engineering and Computer Science Poland
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