@MastersThesis{Svec2001,
  UPDATE  = { 2003-06-26 },
  Author =       {{\v S}vec, Martin},
  School =       {Czech Technical University, Faculty of Electrical
                  Engineering, Department of Cybernetics},
  Title =        {Analysis of Sonographic Images of Thyroid Gland
                  Based on Texture Classification },
  Address =      {Prague, Czech republic},
  Year =         {2001},
  Month =        {June},
  Day =          {19},
  Supervisor =   {{\v S}{\'a}ra, Radim},
  Annote =       {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.},
  keywords =     {sonographic image, thyroid gland, quantitative analysis,
                  haralick features, texture classification},
  Pages =        {44},
  Hardcopy =     {CMP.techrep.T353},
  Project =      {NB 5472-3},
}