Abstract #1386

High Resolution PET/MR Imaging Using Anatomical Priors & Motion Correction

Mehdi Khalighi¹, Timothy Deller², Floris Jansen², Mackenzie Carlson³, Tyler Toueg⁴, Steven Tai Lai¹, Dawn Holley¹, Kim Halbert¹, Elizabeth Mormino⁴, Jong Yoon¹, Greg Zaharchuk¹, and Michael Zeineh¹

¹Radiology, Stanford University, Stanford, CA, United States, ²Engineering Dept., GE Healthcare, Waukesha, WI, United States, ³Bioengineering, Stanford University, Stanford, CA, United States, ⁴Neurology, Stanford University, Stanford, CA, United States

Using the anatomical priors in PET image reconstruction by exploiting the correlation between similar voxels in addition to the correlation between neighboring voxels to control noise, will improve the image quality and resolution. However, motion can degrade the outcome if they anatomical priors are not perfectly registered with PET images. Here we have combined PET image reconstruction with anatomical priors and rigid motion correction for PET/MR brain images to address this. The results show improved image resolution in addition to higher signal-to-noise ratio.

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