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Akinori Hata

Showing results (21-30 of 63) with videos related to

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Journal of Clinical Medicine|September 9, 2023
Usefulness of Three-Dimensional Iodine Mapping Quantified by Dual-Energy CT for Differentiating Thymic Epithelial TumorsShuhei Doi, Masahiro Yanagawa, Takahiro Matsui, et al.
European Radiology|February 20, 2020
Influence of field of view size on image quality: ultra-high-resolution CT vs. conventional high-resolution CTTomo Miyata, Masahiro Yanagawa, Akinori Hata, et al.
Clinical Lung Cancer|November 26, 2024
Radiologists Versus AI-Based Software: Predicting Lymph Node Metastasis and Prognosis in Lung Adenocarcinoma From CT Under Various Image Display ConditionsJunya Sato, Masahiro Yanagawa, Daiki Nishigaki, et al.
Radiographics : a Review Publication of the Radiological Society of North America, Inc|September 9, 2022
Interstitial Lung Abnormalities at CT: Subtypes, Clinical Significance, and Associations with Lung CancerAkinori Hata, Takuya Hino, Masahiro Yanagawa, et al.
Medicine|March 16, 2017
Radiological prediction of tumor invasiveness of lung adenocarcinoma on thin-section CTMasahiro Yanagawa, Takeshi Johkoh, Masayuki Noguchi, et al.
European Journal of Radiology Open|June 18, 2021
Quantitative volumetry of ground-glass nodules on high-spatial-resolution CT with 0.25-mm section thickness and 1024 matrix: Phantom and clinical studiesYuriko Yoshida, Masahiro Yanagawa, Akinori Hata, et al.
Cancer Imaging : the Official Publication of the International Cancer Imaging Society|January 20, 2021
Interstitial lung abnormalities in patients with stage I non-small cell lung cancer are associated with shorter overall survival: the Boston lung cancer studyTomoyuki Hida, Akinori Hata, Junwei Lu, et al.
Medicine|June 25, 2019
Application of deep learning (3-dimensional convolutional neural network) for the prediction of pathological invasiveness in lung adenocarcinoma: A preliminary studyMasahiro Yanagawa, Hirohiko Niioka, Akinori Hata, et al.
Journal of Thoracic Disease|June 13, 2022
CT-based radiomics analysis for differentiation between thymoma and thymic carcinomaRyosuke Ohira, Masahiro Yanagawa, Yuki Suzuki, et al.
European Radiology|June 25, 2022
Radiologists with and without deep learning-based computer-aided diagnosis: comparison of performance and interobserver agreement for characterizing and diagnosing pulmonary nodules/massesTomohiro Wataya, Masahiro Yanagawa, Mitsuko Tsubamoto, et al.
Pageof 7

Showing results (21-30 of 63) with videos related to

Sort By:
Pageof 7
Journal of Clinical Medicine|September 9, 2023
Usefulness of Three-Dimensional Iodine Mapping Quantified by Dual-Energy CT for Differentiating Thymic Epithelial TumorsShuhei Doi, Masahiro Yanagawa, Takahiro Matsui, et al.
European Radiology|February 20, 2020
Influence of field of view size on image quality: ultra-high-resolution CT vs. conventional high-resolution CTTomo Miyata, Masahiro Yanagawa, Akinori Hata, et al.
Clinical Lung Cancer|November 26, 2024
Radiologists Versus AI-Based Software: Predicting Lymph Node Metastasis and Prognosis in Lung Adenocarcinoma From CT Under Various Image Display ConditionsJunya Sato, Masahiro Yanagawa, Daiki Nishigaki, et al.
Radiographics : a Review Publication of the Radiological Society of North America, Inc|September 9, 2022
Interstitial Lung Abnormalities at CT: Subtypes, Clinical Significance, and Associations with Lung CancerAkinori Hata, Takuya Hino, Masahiro Yanagawa, et al.
Medicine|March 16, 2017
Radiological prediction of tumor invasiveness of lung adenocarcinoma on thin-section CTMasahiro Yanagawa, Takeshi Johkoh, Masayuki Noguchi, et al.
European Journal of Radiology Open|June 18, 2021
Quantitative volumetry of ground-glass nodules on high-spatial-resolution CT with 0.25-mm section thickness and 1024 matrix: Phantom and clinical studiesYuriko Yoshida, Masahiro Yanagawa, Akinori Hata, et al.
Cancer Imaging : the Official Publication of the International Cancer Imaging Society|January 20, 2021
Interstitial lung abnormalities in patients with stage I non-small cell lung cancer are associated with shorter overall survival: the Boston lung cancer studyTomoyuki Hida, Akinori Hata, Junwei Lu, et al.
Medicine|June 25, 2019
Application of deep learning (3-dimensional convolutional neural network) for the prediction of pathological invasiveness in lung adenocarcinoma: A preliminary studyMasahiro Yanagawa, Hirohiko Niioka, Akinori Hata, et al.
Journal of Thoracic Disease|June 13, 2022
CT-based radiomics analysis for differentiation between thymoma and thymic carcinomaRyosuke Ohira, Masahiro Yanagawa, Yuki Suzuki, et al.
European Radiology|June 25, 2022
Radiologists with and without deep learning-based computer-aided diagnosis: comparison of performance and interobserver agreement for characterizing and diagnosing pulmonary nodules/massesTomohiro Wataya, Masahiro Yanagawa, Mitsuko Tsubamoto, et al.
Pageof 7