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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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