TY - JOUR
T1 - A segmentation problem in quantitative assessment of organ disposition in radiotherapy
AU - Naldi, Giovanni
AU - Avuzzi, Barbara
AU - Fantini, Simona
AU - Carrara, Mauro
AU - Orlandi, Ester
AU - Massafra, Elisa
AU - Tomatis, Stefano
PY - 2011
Y1 - 2011
N2 - 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 radiotherapy techniques 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., 2010; 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 nonlinear diffusion filter is applied; a level set based method for extract 2D countours; a postprocessing reconstruction of 3D volume from 2D segmented slices. Some comparisons with manually traced segmentation by clinical experts are provided.
AB - 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 radiotherapy techniques 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., 2010; 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 nonlinear diffusion filter is applied; a level set based method for extract 2D countours; a postprocessing reconstruction of 3D volume from 2D segmented slices. Some comparisons with manually traced segmentation by clinical experts are provided.
KW - 3D reconstruction
KW - Geometrical features
KW - Level set
KW - Radiotherapy planning
KW - Segmentation
UR - http://www.scopus.com/inward/record.url?scp=84856892636&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84856892636&partnerID=8YFLogxK
U2 - 10.5566/ias.v30.p179-186
DO - 10.5566/ias.v30.p179-186
M3 - Article
AN - SCOPUS:84856892636
VL - 30
SP - 179
EP - 186
JO - Image Analysis and Stereology
JF - Image Analysis and Stereology
SN - 1580-3139
IS - 3
ER -