Generation of MR-based Attenuation Correction Map of PET Images in the Brain Employing Joint Segmentation of Skull and Soft Tissue from Single Short-TE MR Imaging Modality

 

Abstract

Recently introduced PET/MRI scanners present significant advantages in comparison with PET/CT, including better soft-tissue contrast, lower radiation dose, and truly simultaneous imaging capabilities. However, the lack of an accurate method for generation of MR-based attenuation map (μμ-map) at 511 keV is hampering further development and wider acceptance of this technology. Here, we present a new method for the MR-based attenuation correction map (μμ-map), employing a proposed short echo-time (STE) MR imaging technique along with the nearly automatic segmentation. This method repeatedly applies active contours inhomogeneity correction, multi-class spatial fuzzy clustering (SFCM), followed by shape analysis, to classify the images into cortical bone, air, and soft tissue classes. The proposed segmentation method returned sensitivity of 81 % for cortical bone and above 90 % for soft tissue and air. These results suggest that this technique is accurate, efficient, and robust for discriminating bony structures from the neighboring air and soft tissue in STE-MR images, which is suitable for generating MR-based μμ-maps.

Keywords:

PET/MRI, Short echo-time (STE) MRI, Attenuation correction, Inhomogeneity correction, Shape analysis, Spatial fuzzy clustering.
Authors:

A Fathi Kazerooni, MH A’arabi, M Ay and H Saligheh Rad .
Conference:

MICCAI 2014 Workshop on Computational Methods for Molecular Imaging (CMMI’14), September 14, 2014, Massachusetts Institute of Technology (MIT) in Cambridge Mass., USA.
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