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Different types of image texture features in ultrasound of patients with lymphocytic thyroiditis
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Source ACM International Conference Proceeding Series; Vol. 49 archive
Proceedings of the 1st international symposium on Information and communication technologies table of contents
Dublin, Ireland
SESSION: Image processing table of contents
Pages: 100 - 102  
Year of Publication: 2003
Authors
Daniel Smutek  Charles University Prague, Czech Republic
Radim Sara  University Prague, Czech Republic
Petr Sucharda  Charles University Prague, Czech Republic
Ludvik Tesar  Institute of Information Theory and Automation of the Academy of Sciences of the Czech Republic, Prague, Czech Republic
Publisher
Trinity College Dublin 
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ABSTRACT

Ultrasound is very important imaging modality in diagnosing and monitoring diseases of thyroid gland. We propose using quantifiable indices for texture characterization and classification. Spatial features, co-occurrence texture features, and non-heuristic texture features are compared in this study. The spatial texture features acted as the best descriptors of changed thyroid tissue for texture characterization with a classification success rate of 100%. The co-occurrence features achieved the classification success about 75% and required to be in a group of four or eight features. The results of non-heuristic texture features were on the border between spatial and co-occurrence features. The overall good classification results confirm that the information related to diagnosis can be adequately extracted from sonographic images of subsurface organs. Quantitative indicators enable reproducibility of the sonographic diagnosis, facilitate assessment of changes of the disease and make possible the comparison of different physicians' findings of a sonographic examination.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
1
Devroye L., Gyorfi L., Lugosi G. A. Probabilistic Theory of Pattern Recognition. New York: Springer Verlag, 1996.
 
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Muzzolini R., Yang YH, Pierson R. Texture characterization using robust statistics. Pattern Recognition 1994; 27(1):119--134
 
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Haralick R. M. and L. G. Shapiro. Computer and Robot Vision, volume 1, chapter Texture. Addison-Wesley Publishing Company, 1993, pp. 453--507
 
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Wartfsky L., Ingbar SH: Disease of the Thyroid. In: Harrison's principles of internal medicine, 12th ed., McGraw-Hill Inc., New York 1991, p. 1712
Collaborative Colleagues:
Daniel Smutek: colleagues
Radim Sara: colleagues
Petr Sucharda: colleagues
Ludvik Tesar: colleagues