In recent years, magnetic resonance imaging (MRI) systems that operate up to under 3T are being used in clinical practice in Japan. In order to achieve the requirements of higher image quality and shorter imaging times, devices that utilize high magnetic fields (> 3T) and high power electromagnetic (EM) wave pulses have been developed. The rise of the static magnetic field is proportional to the increase of the EM wave frequency which raises the issue of variation in capacitance used in the radio frequency (RF) coil for MRI system. In addition, increasing power causes problems of withstanding voltage and these approaches leads to generation of non-uniform magnetic field inside the RF coil. Therefore, we proposed a birdcage coil without the use of lumped circuit elements for MRI systems in previous study. However, it is difficult to fabricate this birdcage coil. Hence, simply-structured birdcage coil with no lumped circuit elements is desired. In this paper, we propose a simply-structured birdcage coil with no lumped circuit elements for a 4T MRI system. In addition, the authors investigated the input impedance and magnetic field distribution of the proposed coil by FDTD calculations and measurements. The results confirm that the proposed birdcage coil matches the performance of the conventional birdcage coil which includes several capacitors.

This paper presents the computational electromagnetic dosimetry inside an anatomically based pregnant woman models exposed to electromagnetic wave during magnetic resonance imaging. The two types of pregnant woman models corresponding to early gestation and 26 weeks gestation were used for this study. The specific absorption rate (SAR) in and around a fetus were calculated by radiated electromagnetic wave from highpass and lowpass birdcage coil. Numerical calculation results showed that high SAR region is observed at the body in the vicinity of gaps of the coil, and is related to concentrated electric field in the gaps of human body such as armpit and thigh. Moreover, it has confirmed that the SAR in the fetus is less than International Electrotechnical Commission limit of 10 W/kg, when whole-body average SARs are 2 W/kg and 4 W/kg, which are the normal operating mode and first level controlled operating mode, respectively.

For future adaptive networking services, it will be effective if autonomous agents utilize widely spread information that continuously changes. A communication network should provide a framework for agents to utilize information in a large-scale network and should positively support communications among agents. This paper proposes EcAgent (Environment for Communities of Agents). EcAgent provides agents with access to communities that are loose collections of agents. It gathers global information about communications among all agents and makes the agents share it in communities. It makes possible adaptive networking services that use various types of information. We implemented the EcAgent execution environment and some experimental applications to make an adaptive networking service. We also implemented a simulation system to evaluate how accurately the library recognized the embedded relationships as communities. The results of experiments show that the proposed methods for community recognition work efficiently.

This paper deals with a method of registration and superimposition of a coronary arterial tree on a myocardial SPECT (Single Photon Emission Computed Tomography) image. We can grasp the myocardial function more easily in connection with the shape of the coronary arterial tree. The superimposed image is easily obtainable through some manual pointing on coronary angiograms (CAG) followed by an automatic matching method: First, a rough shape model of left ventricle is estimated by using SPECT data. This 3-D left ventricular model is projected on a pair of bi-plane CAG images. We can obtain two 2-D coronary images on bull's eye map by scanning the left ventricular surface projected on CAG. By maximizing a matching degree between two 2-D coronary images, registration between CAG and SPECT is performed. Finally the superimposed image is obtained by integrating two 2-D coronary images and bull's eye image of SPECT. We validated our method by numerical experiments with artificial data set and also applied it to two clinical data sets.