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Non-rigid registrat...
Non-rigid registration methods assessment of 3D CT images for head-neck radiotherapy
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- Parraga, Adriane (författare)
- Dept. of Electrical Engineering, Federal University of Rio Grande do Sul, Av. Osvaldo Aranha, Porto Alegre, Brazil and Dept. of Electrical Engineering, Universit´e Catholique de Louvain, Belgium
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- Pettersson, Johanna, 1977- (författare)
- Linköpings universitet,Medicinsk informatik,Tekniska högskolan
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- Susin, Altamiro (författare)
- Dept. of Electrical Engineering, Federal University of Rio Grande do Sul, Av. Osvaldo Aranha, Porto Alegre, Brazil
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- De Craene, Mathieu (författare)
- Dept. of Technology, Pompeu Fabra University, Barcelona, Spain
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- Marq, Benoît (författare)
- Dept. of Electrical Engineering, Universit´e Catholique de Louvain, Belgium
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Dept of Electrical Engineering, Federal University of Rio Grande do Sul, Av. Osvaldo Aranha, Porto Alegre, Brazil and Dept. of Electrical Engineering, Universit´e Catholique de Louvain, Belgium Medicinsk informatik (creator_code:org_t)
- SPIE - International Society for Optical Engineering, 2007
- 2007
- Engelska.
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Ingår i: Medical Imaging 2007. - : SPIE - International Society for Optical Engineering. - 9780819466303 ; , s. 6512H1-6512H9
- Relaterad länk:
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https://urn.kb.se/re...
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https://doi.org/10.1...
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Abstract
Ämnesord
Stäng
- Intensity Modulated Radiotherapy is a new technique enabling the sculpting of the 3D radiation dose. It enables to modulate the delivery of the dose inside the malignant areas and constrain the radiation plan for protecting important functional areas. It also raises the issues of adequacy and accuracy of the selection and delineation of the target volumes. The delineation in the patient image of the tumor volume is highly time-consuming and requires considerable expertise. In this paper we focus on atlas based automatic segmentation of head and neck patients and compare two non-rigid registration methods: B-Spline and Morphons. To assess the quality of each method, we took a set of four 3D CT patient's images previously segmented by a doctor with the organs at risk. After a preliminary affine registration, both non-rigid registration algorithms were applied to match the patient and atlas images. Each deformation field, resulted from the non-rigid deformation, was applied on the masks corresponding to segmented regions in the atlas. The atlas based segmentation masks were compared to manual segmentations performed by an expert. We conclude that Morphons has performed better for matching all structures being considered, improving in average 11% the segmentation.
Nyckelord
- MEDICINE
- MEDICIN
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