title: Single STE-MR Acquisition in MR-Based Attenuation Correction of Brain PET Imaging Employing a Fully Automated and Reproducible Level-Set Segmentation Approach.
abstract: 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.
  
  
  
  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.
  
  
  
  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.
  
  
  
  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.
authors.affiliation: Quantitative MR Imaging and Spectroscopy Group (QMISG), Research Center for Molecular and Cellular Imaging (RCMCI), Tehran University of Medical Sciences, Tehran, Iran.|Department of Medical Physics and Biomedical Engineering, Tehran University of Medical Sciences, Tehran, Iran.
authors.forename: Anahita
authors.initials: A
authors.lastname: Fathi Kazerooni
authors.affiliation: Department of Medical Physics and Biomedical Engineering, Tehran University of Medical Sciences, Tehran, Iran.|Medical Imaging Systems Group (MISG), Research Center for Molecular and Cellular Imaging (RCMCI), Tehran University of Medical Sciences, Tehran, Iran.
authors.forename: Mohammad Reza
authors.initials: MR
authors.lastname: Ay
authors.affiliation: College of Letters and Science, Department of Molecular and Cell Biology, University of California, Berkeley, USA.
authors.forename: Saman
authors.initials: S
authors.lastname: Arfaie
authors.affiliation: Medical Imaging Systems Group (MISG), Research Center for Molecular and Cellular Imaging (RCMCI), Tehran University of Medical Sciences, Tehran, Iran.
authors.forename: Parisa
authors.initials: P
authors.lastname: Khateri
authors.affiliation: Quantitative MR Imaging and Spectroscopy Group (QMISG), Research Center for Molecular and Cellular Imaging (RCMCI), Tehran University of Medical Sciences, Tehran, Iran. h-salighehrad@tums.ac.ir.|Department of Medical Physics and Biomedical Engineering, Tehran University of Medical Sciences, Tehran, Iran. h-salighehrad@tums.ac.ir.
authors.forename: Hamidreza
authors.initials: H
authors.lastname: Saligheh Rad
mesh_terms: D001331:Automation; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008279:Magnetic Resonance Imaging / Q000379:methods*; D064847:Multimodal Imaging; D049268:Positron-Emission Tomography / Q000379:methods*; D015203:Reproducibility of Results; D013997:Time Factors; D014057:Tomography, X-Ray Computed
keywords: Attenuation correction; Attenuation map; Level-set technique; PET/MRI; STE-MRI