Patient motion due to respiration can lead to artefacts and blurring in positron emission tomography (PET) images, in addition to quantification errors. The integration of PET with magnetic resonance (MR) imaging in PET-MR scanners provides complementary clinical information, and allows the use of high spatial resolution and high contrast MR images to monitor and correct motion-corrupted PET da...

In this paper, the effect of mathematical representation method of an MR damper on the performance of control algorithm is investigated. The most exact and common Maxwel Nonlinear Slider (MNS) and modified Bouc-Wen hysteretic models are employed through a nonlinear  comparatve numerical study. In many of semi-active control algorithms, a mathematical modelling method is required for determinig ...

I was only a child when Dr Carleton Gajdusek, Michael Alpers and Shirley Lindenbaum conducted research on kuru in the South Fore. They patrolled around the villages and saw how many of our people were dying of kuru and the number of orphans in our villages. My late brother, Mr Animo Kaguya, was the only member of our family involved in the early research on kuru; he assisted in carrying equipme...

Introduction: Radiation therapy planning (RTP) is one of the clinical applications in which both CT scan and MRI are used. MR and CT images are applied to determine the target volume and calculation of dose distribution, respectively. In addition, using two imaging modalities increases the department workload and cost. In this study, an algorithm was presented to create synthet...

Patient motion due to respiration can lead to artefacts and blurring in positron emission tomography (PET) images, in addition to quantification errors. The integration of PET with magnetic resonance (MR) imaging in PET-MR scanners provides complementary clinical information, and allows the use of high spatial resolution and high contrast MR images to monitor and correct motion-corrupted PET da...

In recommender systems, a common problem is the presence of various biases in collected data, which deteriorates generalization ability recommendation models and leads to inaccurate predictions. Doubly robust (DR) learning has been studied many tasks RS, with advantage that unbiased can be achieved when either single imputation or propensity model accurate. this paper, we propose multiple (MR) ...