Zobrazeno 1 - 10 of 95 pro vyhledávání: '"Ken'ichi Morooka"'
1
Akademický článek
Artificial intelligence to detect noise events in remote monitoring data
Autor: Nobuhiro Nishii, Kensuke Baba, Ken'ichi Morooka, Haruto Shirae, Tomofumi Mizuno, Takuro Masuda, Akira Ueoka, Saori Asada, Masakazu Miyamoto, Kentaro Ejiri, Satoshi Kawada, Koji Nakagawa, Kazufumi Nakamura, Hiroshi Morita, Shinsuke Yuasa
Publikováno v: Journal of Arrhythmia, Vol 40, Iss 3, Pp 560-577 (2024)
Abstract Background Remote monitoring (RM) of cardiac implantable electrical devices (CIEDs) can detect various events early. However, the diagnostic ability of CIEDs has not been sufficient, especially for lead failure. The first notification of lea
Externí odkaz: https://doaj.org/article/6cc3cec35dba45188dcb94d2ec13bac5
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2
Akademický článek
An Informationally Structured Room for Robotic Assistance
Autor: Tokuo Tsuji, Oscar Martinez Mozos, Hyunuk Chae, Yoonseok Pyo, Kazuya Kusaka, Tsutomu Hasegawa, Ken'ichi Morooka, Ryo Kurazume
Publikováno v: Sensors, Vol 15, Iss 4, Pp 9438-9465 (2015)
The application of assistive technologies for elderly people is one of the most promising and interesting scenarios for intelligent technologies in the present and near future. Moreover, the improvement of the quality of life for the elderly is one o
Externí odkaz: https://doaj.org/article/f50d4942cc7441668a9f81568c0e83fa
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3
Akademický článek
Floor Sensing System Using Laser Reflectivity for Localizing Everyday Objects and Robot
Autor: Yoonseok Pyo, Tsutomu Hasegawa, Tokuo Tsuji, Ryo Kurazume, Ken'ichi Morooka
Publikováno v: Sensors, Vol 14, Iss 4, Pp 7524-7540 (2014)
This paper describes a new method of measuring the position of everyday objects and a robot on the floor using distance and reflectance acquired by laser range finder (LRF). The information obtained by this method is important for a service robot wor
Externí odkaz: https://doaj.org/article/cef7846cde95431c9d26bf9998c5406a
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8
A Deep Learning-Based Method for Predicting Volumes of Nasopharyngeal Carcinoma for Adaptive Radiation Therapy Treatment
Autor: Ryo Kurazume, Wafa Mnejja, Bilel Daoud, Leila Farhat, Ken'ichi Morooka, Shoko Miyauchi, Jamel Daoud
Publikováno v: ICPR
This paper presents a new system for predicting the spatial change of Nasopharyngeal carcinoma(NPC) and organ-at-risks (OARs) volumes over the course of the radiation therapy (RT) treatment for facilitating the workflow of adaptive radiotherapy. The
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::6c0467818fa312cffdacc6660e25555c
https://doi.org/10.1109/icpr48806.2021.9412924
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10
A Method for Predicting Dose Distribution of Nasopharyngeal Carcinoma Cases by Multiple Deep Neural Networks
Autor: Leila Farhat, Jamel Daoud, Ryo Kurazume, Shoko Miyauchi, Ken'ichi Morooka, Wafa Mnejja, Bilel Daoud
Publikováno v: 2020 Joint 9th International Conference on Informatics, Electronics & Vision (ICIEV) and 2020 4th International Conference on Imaging, Vision & Pattern Recognition (icIVPR).
In this paper, we propose a method for predicting dose distribution images of patients with Nasopharyngeal carcinoma (NPC) from contoured computer tomography (CT) images. The proposed system is based on our previous method [1]. The first phase is to
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::d63861505953f18ab3cf84020b92148c
https://doi.org/10.1109/icievicivpr48672.2020.9306610
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