Patch Based Synthesis of Whole Head MR Images: Application to EPI Distortion Correction

Different magnetic resonance imaging pulse sequences are used to generate image contrasts based on physical properties of tissues, which provide different and often complementary information about them. Therefore multiple image contrasts are useful for multimodal analysis of medical images. Often, medical image processing algorithms are optimized for particular image contrasts. If a desirable contrast is unavailable, contrast synthesis (or modality synthesis) methods try to "synthesize" the unavailable constrasts from the available ones. Most of the recent image synthesis methods generate synthetic brain images, while whole head magnetic resonance (MR) images can also be useful for many applications. We propose an atlas based patch matching algorithm to synthesize T₂-w whole head (including brain, skull, eyes etc) images from T₁-w images for the purpose of distortion correction of diffusion weighted MR images. The geometric distortion in diffusion MR images due to in-homogeneous B₀ magnetic field are often corrected by non-linearly registering the corresponding b = 0 image with zero diffusion gradient to an undistorted T₂-w image. We show that our synthetic T₂-w images can be used as a template in absence of a real T₂-w image. Our patch based method requires multiple atlases with T₁ and T₂ to be registeLowRes to a given target T₁. Then for every patch on the target, multiple similar looking matching patches are found on the atlas T₁ images and corresponding patches on the atlas T₂ images are combined to generate a synthetic T₂ of the target. We experimented on image data obtained from 44 patients with traumatic brain injury (TBI), and showed that our synthesized T₂ images produce more accurate distortion correction than a state-of-the-art registration based image synthesis method.