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Open Access Publications from the University of California

Tissue Segmentation and Classification for PET/MR MR-based Attenuation Correction Using Zero-echo Time (ZTE) MRI

  • Author(s): Leynes, Andrew
  • Advisor(s): Larson, Peder
  • et al.
Abstract

To reduce errors in the reconstructed PET image, the photon attenuation of all tissues needs to be accounted for. Current sequence-based methods to generate an MR-derived attenuation map are unable to account for all tissue classes. Recent work has demonstrated that there is phase contrast in ultrashort echo time (UTE) or zero echo time (ZTE) images that would allow classification of all necessary tissue classes (bone, air, fat, and water) from only a single ZTE scan. The aim of this thesis is to demonstrate the feasibility of generating a pseudo-CT attenuation map based on bone, air, fat, and water classifications from a single ZTE acquisition. A 3D image of the pelvis was acquired using a ZTE pulse sequence on a 3T GE Signa PET/MRI system. Semi-automated algorithms were used to segment bone, air, and soft tissue from the ZTE magnitude image. Air was segmented using an intensity limited region growing algorithm and global thresholding. Bone was segmented by enhancing bone, and then using global thresholding. Soft tissue was defined as regions where bone and air were absent. A continuous-value fat/water map was then generated with fuzzy c-means clustering using the ZTE phase image and the soft tissue mask. Appropriate HU values were assigned to the segmented tissue maps, and combined to produce the pseudo-CT attenuation map. Qualitative comparisons with CT, and Dixon pseudo-CT images presented similar tissue classification results. Preliminary results demonstrate that bone, air, fat, and water can be classified using a single ZTE acquisition.

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