Analysis of Sonographic Images of Thyroid Gland Based on Texture Classification Master’s Thesis
نویسنده
چکیده
Classification from sonographic images of thyroid gland is tackled in semiautomatic way. While making manual diagnosis from images, some relevant information need not to be recognized by human visual system. Quantitative image analysis could be helpful to manual diagnostic process so far done by physician. Two classes are considered: normal tissue and chronic lymphocytic thyroiditis (Hashimoto’s Thyroiditis). Data are represented by Haralick features and 1-dimensional histograms. Data structure is analyzed using K-nearest-neighbour classification. Conclusion of this thesis is that unlike the histograms, Haralick features are not appropriate to distinguish between normal tissue and Hashimoto’s thyroiditis.
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