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European Journal of Radiology
|
October 11, 2011
Pulmonary nodules: effect of adaptive statistical iterative reconstruction (ASIR) technique on performance of a computer-aided detection (CAD) system-comparison of performance between different-dose CT scans
Masahiro Yanagawa, Osamu Honda, Ayano Kikuyama, et al.
Academic Radiology
|
July 17, 2010
Adaptive statistical iterative reconstruction technique for pulmonary CT: image quality of the cadaveric lung on standard- and reduced-dose CT
Masahiro Yanagawa, Osamu Honda, Shigeyuki Yoshida, et al.
Acta Radiologica (Stockholm, Sweden : 1987)
|
October 5, 2011
Detection of pulmonary nodules by C-arm CT using a phantom lung: comparison with CT
Hiroki Higashihara, Keigo Osuga, Takeo Azuma, et al.
Journal of Bronchology & Interventional Pulmonology
|
November 22, 2012
A feasibility and efficacy study on bronchoscopy with a virtual navigation system
Hideyasu Omiya, Ayano Kikuyama, Akihito Kubo, et al.
Radiology
|
May 27, 2010
Multidetector CT of the lung: image quality with garnet-based detectors
Masahiro Yanagawa, Noriyuki Tomiyama, Osamu Honda, et al.
Journal of Computer Assisted Tomography
|
September 19, 2013
The effect of the virtual monochromatic spectral imaging for the metallic artifact and the pulmonary nodule detection
Tomoko Gyobu, Osamu Honda, Yutaka Kawata, et al.
Academic Radiology
|
April 20, 2010
CT-guided percutaneous cutting needle biopsy of thymic epithelial tumors comparison to the accuracy of computed tomographic diagnosis according to the world health organization classification
Masahiro Yanagawa, Noriyuki Tomiyama, Osamu Honda, et al.
Academic Radiology
|
January 7, 2012
Lung image quality with 320-row wide-volume CT scans: the effect of prospective ECG-gating and comparisons with 64-row helical CT scans
Tsuneo Yamashiro, Tetsuhiro Miyara, Masashi Takahashi, et al.
Scientific Reports
|
January 19, 2024
"KAIZEN" method realizing implementation of deep-learning models for COVID-19 CT diagnosis in real world hospitals
Naoki Okada, Yutaka Umemura, Shoi Shi, et al.
Page
of 1
Search research articles
Search
Showing results (1-10 of 9) with videos related to
Sort By:
Page
of 1
European Journal of Radiology
|
October 11, 2011
Pulmonary nodules: effect of adaptive statistical iterative reconstruction (ASIR) technique on performance of a computer-aided detection (CAD) system-comparison of performance between different-dose CT scans
Masahiro Yanagawa, Osamu Honda, Ayano Kikuyama, et al.
Academic Radiology
|
July 17, 2010
Adaptive statistical iterative reconstruction technique for pulmonary CT: image quality of the cadaveric lung on standard- and reduced-dose CT
Masahiro Yanagawa, Osamu Honda, Shigeyuki Yoshida, et al.
Acta Radiologica (Stockholm, Sweden : 1987)
|
October 5, 2011
Detection of pulmonary nodules by C-arm CT using a phantom lung: comparison with CT
Hiroki Higashihara, Keigo Osuga, Takeo Azuma, et al.
Journal of Bronchology & Interventional Pulmonology
|
November 22, 2012
A feasibility and efficacy study on bronchoscopy with a virtual navigation system
Hideyasu Omiya, Ayano Kikuyama, Akihito Kubo, et al.
Radiology
|
May 27, 2010
Multidetector CT of the lung: image quality with garnet-based detectors
Masahiro Yanagawa, Noriyuki Tomiyama, Osamu Honda, et al.
Journal of Computer Assisted Tomography
|
September 19, 2013
The effect of the virtual monochromatic spectral imaging for the metallic artifact and the pulmonary nodule detection
Tomoko Gyobu, Osamu Honda, Yutaka Kawata, et al.
Academic Radiology
|
April 20, 2010
CT-guided percutaneous cutting needle biopsy of thymic epithelial tumors comparison to the accuracy of computed tomographic diagnosis according to the world health organization classification
Masahiro Yanagawa, Noriyuki Tomiyama, Osamu Honda, et al.
Academic Radiology
|
January 7, 2012
Lung image quality with 320-row wide-volume CT scans: the effect of prospective ECG-gating and comparisons with 64-row helical CT scans
Tsuneo Yamashiro, Tetsuhiro Miyara, Masashi Takahashi, et al.
Scientific Reports
|
January 19, 2024
"KAIZEN" method realizing implementation of deep-learning models for COVID-19 CT diagnosis in real world hospitals
Naoki Okada, Yutaka Umemura, Shoi Shi, et al.
Page
of 1