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• W2001463071 abstract "Abstract The integration of physiological (PET) and anatomical (CT) images in cancer delineation requires an accurate spatial registration technique. Although hybrid PET/CT scanner is used to co-register these images, significant misregistrations exist due to patient and respiratory/cardiac motions. This paper proposes a hybrid feature–intensity based registration technique for hybrid PET/CT scanner. First, simulated PET sinogram was filtered with a 3D hybrid mean–median before reconstructing the image. The features were then derived from the segmented structures (lung, heart and tumor) from both images. The registration was performed based on modified multi-modality demon registration with multiresolution scheme. Apart from visual observations improvements, the proposed registration technique increased the normalized mutual information index (NMI) between the PET/CT images after registration. All nine tested datasets show marked improvements in mutual information (MI) index than free form deformation (FFD) registration technique with the highest MI increase is 25%." @default.
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• W2001463071 date "2015-11-01" @default.
• W2001463071 modified "2023-09-26" @default.
• W2001463071 title "Hybrid registration of PET/CT in thoracic region with pre-filtering PET sinogram" @default.
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• W2001463071 doi "https://doi.org/10.1016/j.radphyschem.2015.01.022" @default.
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