@PhDThesis{Garcia-Arteaga-TR-2012-15,
  IS = { zkontrolovano 16 May 2013 },
  UPDATE  = { 2012-12-27 },
  author =       {Garc{\'\i}a-Arteaga, Juan David},
  supervisor =   {Kybic, Jan},
  title =        {Multichannel Image Information Similarity Measures:
                  Applications to Colposcopy Image Registration},
  school =       {Center for Machine Perception, K13133 FEE Czech Technical
                  University},
  address =      {Prague, Czech Republic},
  year =         {2012},
  month =        {August},
  day =          {31},
  type =         {{PhD Thesis CTU--CMP--2012--15}},
  issn =         {1213-2365},
  pages =        {114},
  figures =      {48},
  authorship =   {100},
  psurl =        {[Garcia-Arteaga-TR-2012-15.pdf]},
  annote =       {This thesis deals with the use of the
    Kozachenko-Leonenko within a complete registration framework. We
    present results in which KL is used to calculate higher-order MI
    for high dimensional multi-spectral images. This method
    outperforms other more widespread similarity criteria in alignment
    tasks while avoiding the artifacts that appear in the similarity
    function due to the discrete nature of the registered
    images. Additionally, we present a practical application of an
    elastic registration algorithm based on KL in cervical cancer
    prevention. The algorithm allows the changes in the acetowhite
    decay level for a sequence of images captured during a colposcopy
    exam to be measured analytically. This permits temporal features
    to be extracted for pixel-wise classification and final results to
    be compared against ground truth histopathological annotations.},
  keywords =     {image registration, colposcopy, cervical cancer, computer
                  aided diagnosis, image similarity, entropy},
}