Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Takamichi Murakami"'
Autor:
Aki Miyazaki, Kengo Ikejima, Mizuho Nishio, Minoru Yabuta, Hidetoshi Matsuo, Koji Onoue, Takaaki Matsunaga, Eiko Nishioka, Atsushi Kono, Daisuke Yamada, Ken Oba, Reiichi Ishikura, Takamichi Murakami
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-12 (2023)
Abstract To evaluate the diagnostic performance of our deep learning (DL) model of COVID-19 and investigate whether the diagnostic performance of radiologists was improved by referring to our model. Our datasets contained chest X-rays (CXRs) for the
Externí odkaz:
https://doaj.org/article/817c4564f22d46c08318f143d2dcdcaa
Autor:
Tianyuan Wang, Keitaro Sofue, Ryuji Shimada, Takeaki Ishihara, Ryuichi Yada, Masanori Miyamoto, Ryohei Sasaki, Takamichi Murakami
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-13 (2023)
Abstract To develop and investigate the feasibility of sub-second temporal resolution volumetric T1-weighted four-dimensional (4D-) MRI in comparison with 4D-CT for respiratory-correlated motion assessment using an MRI/CT-compatible phantom. Sub-seco
Externí odkaz:
https://doaj.org/article/a73c35b25e904926a81f30c089901444
Autor:
Eiko Nishioka, Keitaro Sofue, Koji Maruyama, Eisuke Ueshima, Yoshiko Ueno, Masakatsu Tsurusaki, Shohei Komatsu, Takumi Fukumoto, Takamichi Murakami
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-11 (2023)
Abstract To assess the value of nonenhancing capsule by adding to enhancing capsule in gadoxetic acid-enhanced MRI (EOB-MRI) in comparison with contrast-enhanced CT (CE-CT) for diagnosing histological capsule in hepatocellular carcinoma (HCC). One-hu
Externí odkaz:
https://doaj.org/article/4276c0862aee4694bfe86bdc2fd8fc64
Autor:
Hidetoshi Matsuo, Mizuho Nishio, Munenobu Nogami, Feibi Zeng, Takako Kurimoto, Sandeep Kaushik, Florian Wiesinger, Atsushi K. Kono, Takamichi Murakami
Publikováno v:
Scientific Reports, Vol 12, Iss 1, Pp 1-15 (2022)
Abstract The integrated positron emission tomography/magnetic resonance imaging (PET/MRI) scanner simultaneously acquires metabolic information via PET and morphological information using MRI. However, attenuation correction, which is necessary for q
Externí odkaz:
https://doaj.org/article/3abc55ffc1eb4d1f85753bba5c842add
Autor:
Mizuho Nishio, Daigo Kobayashi, Eiko Nishioka, Hidetoshi Matsuo, Yasuyo Urase, Koji Onoue, Reiichi Ishikura, Yuri Kitamura, Eiro Sakai, Masaru Tomita, Akihiro Hamanaka, Takamichi Murakami
Publikováno v:
Scientific Reports, Vol 12, Iss 1, Pp 1-10 (2022)
Abstract This retrospective study aimed to develop and validate a deep learning model for the classification of coronavirus disease-2019 (COVID-19) pneumonia, non-COVID-19 pneumonia, and the healthy using chest X-ray (CXR) images. One private and two
Externí odkaz:
https://doaj.org/article/3fb6903f49cf4d4cb7f55ba53cbbe0d6