Hybrid registration of PET/CT in thoracic region with pre-filtering PET sinogram. (November 2015)

• Record Type: Journal Article
• Authors: Mokri, S.S.; Saripan, M.I.; Marhaban, M.H.; Nordin, A.J.; Hashim, S.
• Is Part Of: Radiation physics and chemistry. Volume 116(2015:Nov.)
• Page Start: 300
• Page End: 304
• Publication Date: 2015-11
• Subjects: PET/CT -- Hybrid demon registration -- Multi-modalities -- Sinogram filtering; Radiation chemistry -- Periodicals; Radiometry -- Periodicals; Radiation -- Periodicals; Chimie sous rayonnement -- Périodiques; 539.2
• DOI: 10.1016/j.radphyschem.2015.01.022
• Languages: English
• ISSNs: 0969-806X

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%. Highlights: The proposed sinogram filter improves the SNR of the reconstructed image. The proposed sinogram filter predominates both the mean and median filters by concurrently smooth the flat region and restore the edges. A new approach is presented that modifies the traditional mono-modal demon registration technique to cater for multi-modal misregistration case. The proposed demon based registration locally improves the main structures misalignment between the PET/CT images.