32 KB483 KB27 KB200020242011Avuzzi, BarbaraCarrara, MauroFantini, SimonaMassafra, ElisaNaldi, GiovanniOrlandi, EsterTomatis, Stefanoštevilka:3letnik:30str. 179-186ISSN:1580-3139COBISSID:29700569URN:URN:NBN:SI:doc-7LZB7I66enDruštvo za stereologijo in kvantitativno analizo slike, Medicinska fakultetaImage analysis and stereologyImage Processing, Computer-AssistedNeoplasmsNovotvorbeobdelava slikradioterapijaRadioterapija, planiranje z računalnikomRadiotherapyRadiotherapy Planning, Computer-AssistedsegmentacijaSlika, obdelava z računalnikomtumorA segmentation problem in quantitative assessment of organ disposition in radiotherapy|Radiotherapeutic treatment of cancer is best conducted if the prescription dose is given to the tumor while surrounding normal tissues are maximally spared. With the aim to meet these requirements the complexity of radiotherapytechniques have steadily increased under a strong technological impulse, especially in the last decades. One problem involves the rate of the particular disposition of the structures of interest in a patient. Recently the authors (Tomatis et al., 2010č 2011) have proposed a computational approach in order to represent quantitatively the geometrical features of organs at risk, summarized in characteristics of distance, shape and orientation of such organs in respect to the target. A basic problem to solve before to compute the risk index, is the segmentation of the organs involved in the radiotherapy planning. Here we described a 3D segmentation method by using the clinical computed tomography (CT) data of the patients. Our algorithm is based on different steps, a preprocessing phase where a nonlineardiffusion filter is appliedč a level set based method for extract 2D countoursč a postprocessing reconstruction of 3D volume from 2D segmented slices. Some comparisons with manually traced segmentation by clinical expertsare providedTEXTznanstveno časopisjejournalsSlovenian National E-content AggregatorNational and University Library of SloveniaDruštvo za stereologijo in kvantitativno analizo slike