Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Yusuke Saikawa"'
Autor:
Takumasa Tsuji, Yuta Hirose, Kohei Fujimori, Takuya Hirose, Asuka Oyama, Yusuke Saikawa, Tatsuya Mimura, Kenshiro Shiraishi, Takenori Kobayashi, Atsushi Mizota, Jun’ichi Kotoku
Publikováno v:
BMC Ophthalmology, Vol 20, Iss 1, Pp 1-9 (2020)
Abstract Background Classification of optical coherence tomography (OCT) images can be achieved with high accuracy using classical convolution neural networks (CNN), a commonly used deep learning network for computer-aided diagnosis. Classical CNN ha
Externí odkaz:
https://doaj.org/article/2f5c4d459ed9491ea5178bf919019f4c
Autor:
Tsuyoshi Ozawa, Yusuke Saikawa, Tamuro Hayama, Keijiro Nozawa, Keiji Matsuda, Soichiro Ishihara, Jun’ichi Kotoku, Yojiro Hashiguchi
Objective The accuracy of identifying a CRT-response by a pre-operative radiological examination is limited, and another approach is necessary. We constructed endoscopic image-based radiomics classifiers to predict the response of locally advanced re
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::71c74659d6e3d4fa61b7260ed04002cf
https://doi.org/10.21203/rs.3.rs-1717256/v1
https://doi.org/10.21203/rs.3.rs-1717256/v1
Autor:
Kenshiro Shiraishi, Takumasa Tsuji, Takuya Hirose, Atsushi Mizota, Yusuke Saikawa, Takenori Kobayashi, Yuta Hirose, Kohei Fujimori, Asuka Oyama, Tatsuya Mimura, Jun'ichi Kotoku
Publikováno v:
BMC Ophthalmology, Vol 20, Iss 1, Pp 1-9 (2020)
BMC Ophthalmology
BMC Ophthalmology
Background Classification of optical coherence tomography (OCT) images can be achieved with high accuracy using classical convolution neural networks (CNN), a commonly used deep learning network for computer-aided diagnosis. Classical CNN has often b
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::94eeed709af7c8ab0fdd494bb1a87216
http://link.springer.com/article/10.1186/s12886-020-01382-4
http://link.springer.com/article/10.1186/s12886-020-01382-4
Autor:
Shinobu Kumagai, Kenshiro Shiraishi, Jun'ichi Kotoku, Asuka Oyama, Takeshi Takata, Yusuke Saikawa, Takenori Kobayashi, Norikazu Arai
Publikováno v:
Journal of Radiation Research
This study was conducted to improve cone-beam computed tomography (CBCT) image quality using the super-resolution technique, a method of inferring a high-resolution image from a low-resolution image. This technique is used with two matrices, so-calle
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::98c7a19a6b937af321f2ea5c0b776df8
https://doi.org/10.1093/jrr/rry019
https://doi.org/10.1093/jrr/rry019
Autor:
Tatsuya Hayashi, Asuka Oyama, Jun'ichi Kotoku, Yasuaki Hiraoka, Yusuke Saikawa, Kenshiro Shiraishi, Ippei Obayashi, Shigeru Furui, Shinobu Kumagai
Publikováno v:
Scientific Reports, Vol 9, Iss 1, Pp 1-10 (2019)
Scientific Reports
Scientific Reports
The purpose of this study is to evaluate the accuracy for classification of hepatic tumors by characterization of T1-weighted magnetic resonance (MR) images using two radiomics approaches with machine learning models: texture analysis and topological
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fc923d770015c348de76b69427720507
https://doi.org/10.1038/s41598-019-45283-z
https://doi.org/10.1038/s41598-019-45283-z