Generation of 4-Class Attenuation Map for MRI Based Attenuation Correction of PET Data in the Head Area Using a Novel Combination of STE/DIXON-MRI and FCM Clustering

 

Abstract

 

Objective:

The aim of this study is to generate a four-class magnetic resonance imaging (MRI)-based attenuation map (μ-map) for attenuation correction of positron emission tomography (PET) data of the head area using a novel combination of short echo time (STE)/Dixon-MRI and a dedicated image segmentation method.

Results:

The voxel-by-voxel comparison of MR-based and CT-based segmentation results yielded an average of more than 95 % for accuracy and specificity in the cortical bone, soft tissue, and air region. MRI-based μ-maps show a high correlation with those derived from CT scans (R2 90.95).

Conclusion:

Results indicate that STE/Dixon-MRI data in combination with FCM-based segmentation yields precise MR-based μ-maps for PET attenuation correction in hybrid PET/MRI systems.

Keywords:

PET/MRI, Attenuation correction, Attenuation map, STE pulse sequence, FCM technique .
Authors:

Parisa Khateri, Hamidreza Saligheh Rad, AmirHomayoun Jafari, Anahita Fathi Kazerooni, Afshin Akbarzadeh, Mohsen Shojae Moghadam, Arvin Aryan, Pardis Ghafarian, MohammadReza Ay .
Journal:

Molecular Imaging and Biology
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