Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Keisuke Tsuruta"'
Autor:
Keisuke Tsuruta, Toru Ueyama, Tomoo Watanabe, Yasunori Kobata, Kenichi Nakano, Hidetada Fukushima
Publikováno v:
Acute Medicine & Surgery, Vol 10, Iss 1, Pp n/a-n/a (2023)
Abstract Aim The diagnosis of acute vertebral compression fractures (AVCFs) is often challenging. An alternative to magnetic resonance imaging, which may not always be available, includes a comparison of supine and sitting/standing position radiograp
Externí odkaz:
https://doaj.org/article/fa3b2fda0752428eaca5a22c79a492ef
Publikováno v:
BMC Infectious Diseases, Vol 20, Iss 1, Pp 1-6 (2020)
Abstract Background Vibrio cholerae are oxidase-positive bacteria that are classified into various serotypes based on the O surface antigen. V. cholerae serotypes are divided into two main groups: the O1 and O139 group and the non-O1/non-O139 group.
Externí odkaz:
https://doaj.org/article/cd60bee7f2ac46d3bff3ce5b2cd717a8
Publikováno v:
BMC Infectious Diseases, Vol 20, Iss 1, Pp 1-6 (2020)
BMC Infectious Diseases
BMC Infectious Diseases
Background Vibrio cholerae are oxidase-positive bacteria that are classified into various serotypes based on the O surface antigen. V. cholerae serotypes are divided into two main groups: the O1 and O139 group and the non-O1/non-O139 group. O1 and O1
Autor:
Keisuke Tsuruta, Nobuhiro Kimura, Atsushi Segawa, Naohiro Yoshida, Tatsuya Ichijo, Masaki Okamoto
Publikováno v:
Journal of the Japan Petroleum Institute. 63:70-78
Autor:
Keisuke Tsuruta, Ryusei Haraguchi, Katsuhiko Nishiyama, Takahiro Sawaguchi, Soichiro Yoshimoto
Publikováno v:
Electroanalysis. 31:1150-1154
Autor:
Kentaro Yamamura, Sakura Origuchi, Katsuhiko Nishiyama, Mayu Kataoka, Keisuke Tsuruta, Soichiro Yoshimoto, Natsumi Sawada
Publikováno v:
Electrochemistry. 86:345-348
Autor:
Toshihiro Ihara, Keisuke Tsuruta, Soichiro Yoshimoto, Mizuki Ikeda, Katsuhiko Nishiyama, Hiroshi Shimada, Yusuke Kitamura
Publikováno v:
Electrochemistry. 84:349-353
Publikováno v:
IPSJ Transactions on Computer Vision and Applications. 2:48-58
In this paper, we propose a new wavelet denoising method with edge preservation for digital images. Traditionally, most denoising methods assume additive Gaussian white noise or statistical models; however, we do not make such an assumption here. Bri