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Assessment of the quality of radiotherapy with the use of portal and simulation images - the method and the software

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Quality assessment in external beam radiotherapy necessitates for an efficient and robust tool for comparing the planned and realised geometry of the treatment. Such a tool using the modified Hausdorff distance measure has been developed and successfully introduced to clinical practice. The majority of steps of the method are automatic. The user specifies the share of edge data extracted from the images to be used in calculations, not before, but after these calculations are actually performed. Thus, the results of the choice can be seen immediately. This mechanism makes the method extremely robust against partially erroneous or missing data.
Rocznik
Tom
Strony
MI171--179
Opis fizyczny
Bibliogr. 18 poz., rys.
Twórcy
  • Institute of Fundamental Technological Research, PAS, Warsaw, Poland
  • Holycross Cancer Centre, Kielce, Poland
autor
  • Institute of Fundamental Technological Research, PAS, Warsaw, Poland
  • Holycross Cancer Centre, Kielce, Poland
Bibliografia
  • [1] Aaltonen-Brahme A., Brahme A. et al., Specification of dose delivery in radiation therapy. Acta Oncologica, 36(Supplementum 10), 1977.
  • [2] Borgefors G., Hierarchical chamfer matching: A parametric edge matching algorithm. IEEE Trans. PAMI, 10(6):849–865, 1988.
  • [3] Bronsztejn I. N., Siemiendiajew K. A., Mathematics - Encyclopedic guide (in Polish). Polish Scientific Publishers PWN, Warsaw, 7th edition, 1986.
  • [4] Gottesfeld Brown L., A survey of image registration techniques. ACM Computing Surveys, 24(4):325–376, 1992.
  • [5] Cai J., Chu J. C. H., Saxena A., Lanzl L. H., A simple algorithm for planar image registration in radiation therapy. Med. Phys., 25(6):824–829, 1998.
  • [6] Chetverikov D., Khenokh Y., Matching for shape defect detection. In Proc. Conf. Computer Analysis of Images and Patterns CAIP’99, volume 1689 of LNCS, pages 367–374, Ljubljana, Slovenia, Sept 1999. Springer Verlag.
  • [7] Chmielewski L., The AH line edge detector and the hierarchical Hough transform as detectors of the irradiation field in simulation images. In Proc. Int. Conf. on Computer Vision and Graphics ICCVG 2002, Zakopane, Poland, Sept 25-29, 2002. To be published.
  • [8] Eilersten K., Skretting A., Tenvaassas T. L., Methods for fully automated verification of patient set-up in external beam radiotherapy with polygon shaped fields. Phys. Med. Biol., 39:993–1012, 1994.
  • [9] Gilhuijs K. G. A., El-Gayed A. A. H., Van Herk M., Vijlbrief R. E., An algorithm for automatic analysis of portal images: clinical evaluation for prostate treatments. Radiotherapy and Oncology, 29:261–268, 1993.
  • [10] Gilhuijs K. G. A., Van Herk M., Automatic on-line inspection of patient setup in radiation therapy using digital portal images. Med. Phys., 20(3):667–677, 1993.
  • [11] Giraud L. M., Pouliot J., Maldague X., Zaccarin A., Automatic setup deviation measurements with electronic portal images for pelvic fields. Med. Phys., 25(7):1180–1185, 1998.
  • [12] Gut P., Chmielewski L., Kukołowicz P., Dąbrowski A., Edge-based robust image registration for incomplete and partly erroneous data. In SKARBEK W., editor, Proc. 9th Int. Conf. CAIP 2001, volume 2124 of LNCS, pages 309–316, Warsaw, Poland, Sept 5-8, 2001. Springer Verlag.
  • [13] Huttenlocher D. P., Rucklidge W. J., A multi-resolution technique for comparing images using the Hausdorff distance. In Proc. IEEE Conf. on Computer Vision and Pattern Recognition, pages 705–706, New York, Jun 1993.
  • [14] Lester H., Arrige S. R., A survey of hierarchical non-linear medical image registration. Pattern Recognition, 32:129–149, 1999.
  • [15] Mount D. M., Netanyahu N. S., Le Moigne J., Efficient algorithms for robust feature matching. Pattern Recognition, 32:17–38, 1999.
  • [16] Rucklidge W. J., Efficiently locating objects using the Hausdorff distance. Int. J. Comput. Vision, 24(3):251–270, 1997.
  • [17] Van Den Elsen P. A., Pol E. J. D., Viergever M. A., Medical image matching - a review with classification. ACM Computing Surveys, 24(4):325–376, 1992.
  • [18] Yang G. Z., Burger P., Firmin D. N., Underwood S. R., Structure adaptive anisotropic filtering for magnetic resonance image enhancement. In HLAVÁˇC V., ŠÁRA R., editors, Proc. 6th Int. Conf. Computer Analysis of Images and Patterns CAIP’95, volume 970 of LNCS, pages 384–391, Prague, Czech Republic, Sep 6-8, 1995. Springer Verlag.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-PWA4-0023-0024
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