@InProceedings{Barva-SPIEMI2005,
  IS = { zkontrolovano 02 Dec 2005 },
  UPDATE  = { 2005-02-25 },
  author      = { Barva, Martin and Kybic, Jan and Mari, Jean-Martial and 
                  Cachard, Christian and Hlav{\' a}{\v c}, V{\' a}clav },
  title       = { Automatic Localization of Curvilinear Object in {3D}
		  Ultrasound Images },
  year        = { 2005 },
  pages       = { 455--462 },
  booktitle   = { Medical Imaging 2005: Ultrasonic Imaging and Signal Processing },
  editor      = { Walker, William F. and Emelianov, Stanislav Y. },
  publisher   = { SPIE },
  address     = { Bellingham, Washington, USA },
  isbn        = { 1605-7420 },
  book_pages  = { 525 },
  month       = { February },
  day         = { 15-17 },
  venue       = { San Diego, USA },
  organization= {SPIE International Symposium on Medical Imaging},
  annote = {Utilization of tools during surgical interventions sets
    the problem of their accurate localization within biological
    tissue. The ultrasound imaging represents an inexpensive and a
    flexible approach for a real-time image acquisition of tissue
    structure with metal instruments. There are several difficulties
    involving processing of ultrasound images: Their noisy nature
    makes the localization task difficult; the objects appear
    irregular and incomplete. Our task is to determine the position of
    a curvilinear electrode in biological tissue from a
    three-dimensional ultrasound image. Initially, the data are
    segmented by thresholding and processed with the randomized
    version of the RANSAC (R-RANSAC) algorithm. The curvilinear
    electrode is modeled by a three-dimensional cubic curve. Its shape
    is subject to check using a curvature measure in the hypothesis
    evaluation step of the R-RANSAC algorithm. Subsequently, we
    perform the least squares curve fitting to the data that have been
    marked by the R-RANSAC as the ones corresponding to the sought
    object. The position estimation is optimal with respect to the
    mean square criterion. Finally, the localization of the electrode
    tips is carried out by a hypothesis testing on the distances
    between projections of inliers on the estimated curve. The
    algorithm has been tested on real threedimensional ultrasound
    images of a tissue mimicking phantom with a curvilinear
    object. From the results, we conclude that the method is very
    stable even if the data contain high percentage of outliers. The
    computational cost of the algorithm shows the possibility of
    real-time data processing.},
  keywords = { 3D ultrasound, image-guidance, needle, electrode, 
               localization, curved, RANSAC },
  project  = { 1ET101050403, thesis_with_co-supervision },
  psurl = { [PDF, 331 KB] },
  series      = { Progress in Biomedical Optics and Imaging },
  volume      = { 6 },
  number      = { 27 },
  url         = { ftp://cmp.felk.cvut.cz/pub/cmp/articles/barva/Barva-SPIEMI2005.pdf },
}