Single Ste-Mr Acquisition in Mr-Based Attenuation Correction of Brain Pet Imaging Employing a Fully Automated and Reproducible Level-Set Segmentation Approach Publisher Pubmed



Fathi Kazerooni A^{1, 2} ; Ay MR^{2, 3} ; Arfaie S⁴ ; Khateri P³ ; Saligheh Rad H^{1, 2}
Source: Molecular Imaging and Biology Published:2017

Abstract

Purpose: The aim of this study is to introduce a fully automatic and reproducible short echo-time (STE) magnetic resonance imaging (MRI) segmentation approach for MR-based attenuation correction of positron emission tomography (PET) data in head region. Procedures: Single STE-MR imaging was followed by generating attenuation correction maps (μ-maps) through exploiting an automated clustering-based level-set segmentation approach to classify head images into three regions of cortical bone, air, and soft tissue. Quantitative assessment was performed by comparing the STE-derived region classes with the corresponding regions extracted from X-ray computed tomography (CT) images. Results: The proposed segmentation method returned accuracy and specificity values of over 90 % for cortical bone, air, and soft tissue regions. The MR- and CT-derived μ-maps were compared by quantitative histogram analysis. Conclusions: The results suggest that the proposed automated segmentation approach can reliably discriminate bony structures from the proximal air and soft tissue in single STE-MR images, which is suitable for generating MR-based μ-maps for attenuation correction of PET data. © 2016, World Molecular Imaging Society.