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Committee Date Time Place Paper Title / Authors Abstract Paper #
MI 2017-01-18
11:46		 Okinawa Tenbusu Naha [Short Paper] Comparison of FDG-PET Image and MR Image in differential dementia diagnosis using machine learning
Xiaoyu Wang (Chiba Univ./Tokyo Metropolitan Geriatric Hospital), Muneyuki Sakata, Kenji Ishii (Tokyo Metropolitan Geriatric Hospital), Yuichi Kimura (Tokyo Metropolitan Geriatric Hospital/KINDAI Univ.), Keii Wagatsuma, Kenji Ishibashi, Jun Toyohara (Tokyo Metropolitan Geriatric Hospital), Noriko Yata, Yoshitsugu Manabe (Chiba Univ.) MI2016-78		  [more] MI2016-78
pp.31-32
MI 2013-07-18
15:55		 Miyagi   Quantitative Analysis of Amyloid Deposits in PET/CT Images
Kei Sasaki (Yamagata Univ./National Center of Neurology and Psychiatry), Norihide Maikusa (National Center of Neurology and Psychiatry), Tetsuya Yuasa (Yamagata Univ.), Etsuko Imabayashi (Tokyo Metropolitan Geriatric Hospital), Hiroshi Matsuda (National Center of Neurology and Psychiatry) MI2013-28		 For early diagnosis of Alzheimer’s disease (AD), it is effective to quantitatively evaluate deposits of amyloid into gra... [more] MI2013-28
pp.49-53
MI 2012-07-19
15:40		 Yamagata Yamagata Univ. Bayesian Inference Approach to Visualize Neuroreceptor Density using Positron Emission Tomography without Arterial Blood Sampling
Takahiro Kozawa, Hidekata Hontani (NIT), Kazuya Sakaguchi (Kitasato Univ), Muneyuki Sakata (TMGHIG), Yuichi Kimura (NIRS) MI2012-26		 A Bayesian approach to de-noise tissue time activity curves (tTAC) is proposed in order to quantitatively visualize neur... [more] MI2012-26
pp.29-34
MI 2012-01-19
10:30		 Okinawa   Bayesian Approach for the Denoising to PET Dynamic Data without Arterial Blood Sampling
Takahiro Kozawa, Hidekata Hontani (NIT), Kazuya Sakaguchi (Kitasato Univ), Muneyuki Sakata (TMGHIG), Yuichi Kimura (NIRS) MI2011-79		 In this report, we propose a new method for denoising tissue time activity curve (tTAC) measured from brain PET images. ... [more] MI2011-79
pp.11-16
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