An MRI-based Attenuation Correction Method for Combined PET/MRI Applications.

We are developing MRI-based attenuation correction methods for PET images. PET has high sensitivity but relatively low resolution and little anatomic details. MRI can provide excellent anatomical structures with high resolution and high soft tissue contrast. MRI can be used to delineate tumor boundaries and to provide an anatomic reference for PET, thereby improving quantitation of PET data. Combined PET/MRI can offer metabolic, functional and anatomic information and thus can provide a powerful tool to study the mechanism of a variety of diseases. Accurate attenuation correction represents an essential component for the reconstruction of artifact-free, quantitative PET images. Unfortunately, the present design of hybrid PET/MRI does not offer measured attenuation correction using a transmission scan. This problem may be solved by deriving attenuation maps from corresponding anatomic MR images. Our approach combines image registration, classification, and attenuation correction in a single scheme. MR images and the preliminary reconstruction of PET data are first registered using our automatic registration method. MRI images are then classified into different tissue types using our multiscale fuzzy C-mean classification method. The voxels of classified tissue types are assigned theoretical tissue-dependent attenuation coefficients to generate attenuation correction factors. Corrected PET emission data are then reconstructed using a three-dimensional filtered back projection method and an order subset expectation maximization method. Results from simulated images and phantom data demonstrated that our attenuation correction method can improve PET data quantitation and it can be particularly useful for combined PET/MRI applications.