Attenuation correction (AC) is an essential procedure for accurately quantifying molecular targets in positron emission tomography (PET). As an alternative to computed tomography (CT), a variety of approaches utilizing magnetic resonance (MR) imaging has been implemented. Since most of these are computationally expensive (i.e. take several hours), we improved upon the MaxProb[1] algorithm for use in neuroimaging. 40 paired CTs and T1 weighted MR images from a previous study[2] were normalized to Montreal Neurological Institute space. Each CT was then segmented into air, soft tissue and bone. Subsequently, voxels were assigned the mean attenuation value of CTs corresponding to the most prevalent tissue class. The pseudo-CT template was then transformed to individual space. Finally, further anatomical information was appended to the pseudo-CT with a manufacturer-provided µmap to match the PET field of view. This approach was validated by comparing quantification of the serotonin transporter based on PET with radiotracer [11C]DASB between AC using CT and pseudo-CT in 29 subjects. The mean absolute difference between AC methods across all extracted regions was 1.7%±1.9%(mean±sd)(Figure1). Moreover, computational speed was reduced by a factor of six compared to the use of MaxProb in individual space. Our approach combines the accuracy of the MaxProb algorithm with the computational efficiency of the Boston[3] algorithm. This offers a fast and robust solution, which can easily be implemented into clinical protocols and extended to other radiotracers.[1]Mérida et al. Phys Med Biol 62:2834-2858(2017).[2]Rischka et al. Front Psychol 10(2019).[3]Izquierdo-Garcia et al. J Nuc Med 55:1825-1830(2014).