@misc{oai:repo.qst.go.jp:00064839,
 author = {Kawaguchi, Hiroshi and Tanigawa, Asuka and Suga, Mikio and Hirano, Yoshiyuki and Yoshida, Eiji and Shiraishi, Takahiro and Tanimoto, Katsuyuki and Obata, Takayuki and Ito, Hiroshi and Yamaya, Taiga and 川口 拓之 and 谷川 明日香 and 菅 幹生 and 平野 祥之 and 吉田 英治 and 白石 貴博 and 谷本 克之 and 小畠 隆行 and 伊藤 浩 and 山谷 泰賀},
 month = {Nov},
 note = {The ability to make quantitative measurements of radioactivity is essential for human brain PET. Several attenuation correction methods have been reported for PET/MRI scanners, however, their influence on pixel intensity in reconstructed images has not yet been thoroughly evaluated. In addition, when a transmission scan is unavailable assigning literature values for the attenuation coefficient can be problematic. In this study, we evaluated the effect of these potential problems on human brain 18F-FDG- PET. The results indicate that pixel intensities on reconstructed images depend on the attenuation correction method used. Incorrect assignment of the attenuation coefficient for brain causes a larger error in the measured radioactivity than for bone and soft tissues. Moreover, the influence of an incorrect attenuation coefficient for brain is larger in deep gray matter, such as the striatum and thalamus, than in the occipital and temporal cortices. In contrast, an incorrect attenuation coefficient for bone and superficial soft tissue has a larger influence on cortical pixel intensities than on those in deep gray matter. According to the present results, it is necessary to assign the attenuation coefficients to be within 5% of the true value to achieve an error of within 5% of the true pixel intensity on the reconstructed image. This accuracy is needed when performing PET/MRI on subjects with age-related brain atrophy or brain diseases such as hydrocephalia where the attenuation coefficient can differ from its value in normal subjects., International Forum on Medical Imaging in Asia (IFMIA 2012)},
 title = {Evaluation of MRI-based attenuation correction methods for quantitative human brain PET},
 year = {2012}
}