biostudies-literatureChen KTNIBIB NIH HHS398-407https://www.ebi.ac.uk/biostudies/studies/S-EPMC5285302biostudies-literatureUnknown44(3)<h4>Purpose</h4>To propose an MR-based method for generating continuous-valued head attenuation maps and to assess its accuracy and reproducibility. Demonstrating that novel MR-based photon attenuation correction methods are both accurate and reproducible is essential prior to using them routinely in research and clinical studies on integrated PET/MR scanners.<h4>Methods</h4>Continuous-valued linear attenuation coefficient maps ("μ-maps") were generated by combining atlases that provided the prior probability of voxel positions belonging to a certain tissue class (air, soft tissue, or bone) and an MR intensity-based likelihood classifier to produce posterior probability maps of tissue classes. These probabilities were used as weights to generate the μ-maps. The accuracy of this probabilistEuropean journal of nuclear medicine and molecular imagingOn the accuracy and reproducibility of a novel probabilistic atlas-based generation for calculation of head attenuation maps on integrated PET/MR scanners.PMC5285302T32 EB001680R01 EB014894Chen KTChonde DBIzquierdo-Garcia DCatana CPoynton CBfalseOn the accuracy and reproducibility of a novel probabilistic atlas-based generation for calculation of head attenuation maps on integrated PET/MR scanners.<h4>Purpose</h4>To propose an MR-based method for generating continuous-valued head attenuation maps and to assess its accuracy and reproducibility. Demonstrating that novel MR-based photon attenuation correction methods are both accurate and reproducible is essential prior to using them routinely in research and clinical studies on integrated PET/MR scanners.<h4>Methods</h4>Continuous-valued linear attenuation coefficient maps ("μ-maps") were generated by combining atlases that provided the prior probability of voxel positions belonging to a certain tissue class (air, soft tissue, or bone) and an MR intensity-based likelihood classifier to produce posterior probability maps of tissue classes. These probabilities were used as weights to generate the μ-maps. The accuracy of this probabilist2017-01-01T00:00:00Z2017 Mar2025-04-04T00:10:39.734Z2019-03-26T23:04:04ZS-EPMC52853022757363910.1007/s00259-016-3489-z