@InProceedings{Svec-CVWW04,
  IS = { zkontrolovano 30 Mar 2004 },
  UPDATE  = { 2004-02-16 },
  author =       {{\v S}vec, Martin and {\v S}{\'a}ra, Radim and
                  Smutek, Daniel},
  title =        {Sensitivity Analysis for Reproducibility of
                  Ultrasound Image Classification},
  booktitle =    {Proceedings of the Computer Vision Winter Workshop 2004 (CVWW'04)},
  book_pages =   {236},
  pages =        {89--98},
  year =         {2004},
  month =        {February},
  day =          {4--6},
  editor =       {Sko{\v c}aj, Daniel},
  publisher =    {Slovenian Pattern Recognition Society},
  address =      {Ljubljana, Slovenia},
  venue =        {Piran, Slovenia},
  organization = {University of Ljubljana, Faculty of Computer and
                  Information Science},
  annote =       {Ultrasound B-mode images of thyroid gland
                  were previously analyzed to distinguish normal
                  tissue from inflamed tissue due to Hashimoto's
                  Lymphocytic Thyroiditis. This is a two-class
                  recognition problem. Sensitivity and specificity of
                  100% was reported using Bayesian classifier with
                  optimal texture features. These results were
                  obtained on 99 subjects at a fixed setting of the
                  sonograph, for a given manual thyroid gland
                  segmentation and sonographic scan type
                  (longitudinal, transversal). To evaluate the
                  reproducibility of the method, sensitivity analysis
                  is the topic of this paper. A general method for
                  determining feature sensitivity to variables
                  influencing the scanning process is proposed. Jensen
                  Shannon distances between modified and unmodified
                  inter- and intra-class feature probability
                  distributions capture the changes induced by the
                  variables. It is shown there are stable features
                  insensitive to small sonograph gain changes and
                  gland segmentation. Features computed from
                  transversal scans are less sensitive because they
                  have greater inter-class distance than features
                  computed from the longitudinal scans. The proposed
                  sensitivity evaluation method can be used in other
                  problems with complex and non-linear dependencies on
                  variables that cannot be controlled.},
  keywords =     {sensitivity analysis, ultrasound, texture
                  classification,thyroid gland, quantitative analysis},
  project =      {NO/7742-3, MSM 210000012},
}