Masahiro Kazama

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Depending on the clinical application, it is frequently necessary to tilt the gantry of an x-ray CT system with respect to the patient and couch. For single-slice fan-beam systems, tilting the gantry introduces no errors or artifacts. Most current systems, however, are helical multislice systems with up to 16 slices. The multislice helical reconstruction(More)
Experiments were conducted to confirm the isotropic spatial resolution of multislice CT with a 0.5 mm slice thickness. Isotropic spatial resolution means that the spatial resolution in the transaxial plane (X-Y plane) and that in the longitudinal direction (Z direction) are equivalent. To obtain point spread function (PSF) values in the X-Y-Z directions,(More)
PURPOSE The image noise and image quality of a prototype ultra-high-resolution computed tomography (U-HRCT) scanner was evaluated and compared with those of conventional high-resolution CT (C-HRCT) scanners. MATERIALS AND METHODS This study was approved by the institutional review board. A U-HRCT scanner prototype with 0.25 mm x 4 rows and operating at(More)
We propose a novel system which can transform a recipe into any selected regional style (e.g., Japanese, Mediterranean, or Italian). This system has three characteristics. First the system can identify the degree of dietary style mixture of any selected recipe. Second, the system can visualize such dietary style mixtures using barycentric Newton diagrams.(More)
The cold start problem, frequent with recommender systems, addresses the issue in cases where we don’t know enough about our users (e.g., the user hasn’t rated anything yet, or there are no user activities) in that specific domain. In our paper we present a simple and robust transfer learning approach where we model users’ behavior in a source domain,(More)
Ryutaro Kakinuma, Noriyuki Moriyama, Yukio Muramatsu, Shiho Gomi, Masahiro Suzuki, Hirobumi Nagasawa, Masahiko Kusumoto, Tomohiko Aso, Yoshihisa Muramatsu, Takaaki Tsuchida, Koji Tsuta, Akiko Miyagi Maeshima, Naobumi Tochigi, Shunichi Watanabe, Naoki Sugihara, Shinsuke Tsukagoshi, Yasuo Saito, Masahiro Kazama, Kazuto Ashizawa, Kazuo Awai, Osamu Honda,(More)
In a multi-service environment it is crucial to be able to leverage user behavior from one or more domains to create personalized recommendations in the other domain. In our paper, we present a robust transfer learning approach that successfully captures user behavior across multiple domains. First, we vectorize users and items in each domain independently.(More)
We have developed a recommendation system of companies for new graduates. In this paper, we defined high/low-browsed companies and constructed the recruitment navigation system of the low-browsed companies suitable for each student from the browsing data. Different from traditional recommendations, we need to deal with the problems that the entry(More)
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