Assessment of significance of features acquired from thyroid ultrasonograms in Hashimoto's disease.
BACKGROUND
This paper concerns the analysis of the features obtained from thyroid ultrasound images in left and right transverse and longitudinal sections. In the image analysis, the thyroid lobe is treated as a texture for healthy subjects and patients with Hashimoto's disease. The applied methods of analysis and image processing were profiled to obtain 10 features of the image. Then, their significance in the classification was shown.


METHODS
In this study, the examined group consisted of 29 healthy subjects aged 18 to 60 and 65 patients with Hashimoto's disease. For each subject, four ultrasound images were taken. They were all in transverse and longitudinal sections of the right and left lobe of the thyroid, which gave 376 images in total.


METHODS
10 different features obtained from each ultrasound image were suggested. The analyzed thyroid lobe was marked automatically or manually with a rectangular element.


RESULTS
The analysis of 10 features and the creation for each one of them their own decision tree configuration resulted in distinguishing 3 most significant features. The results of the quality of classification show accuracy above 94% for a non-trimmed decision tree.
Department of Computer Biomedical Systems, University of Silesia, Institute of Computer Science, Sosnowiec, Poland. robert.koprowski@us.edu.pl
Robert
R
Koprowski
Witold
W
Zieleźnik
Zygmunt
Z
Wróbel
Justyna
J
Małyszek
Beata
B
Stępień
Waldemar
W
Wójcik
D000293:Adolescent; D000328:Adult; D016022:Case-Control Studies; D050031:Hashimoto Disease / Q000000981:diagnostic imaging*; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008875:Middle Aged; D013961:Thyroid Gland / Q000000981:diagnostic imaging*; D014463:Ultrasonography; D055815:Young Adult