Works by Hirotaka Ikeda

Results: 19
    1

    Pulmonary MRI with ultra-short TE using single- and dual-echo methods: comparison of capability for quantitative differentiation of non- or minimally invasive adenocarcinomas from other lung cancers with that of standard-dose thin-section CT.

    Published in:
    European Radiology, 2024, v. 34, n. 2, p. 1065, doi. 10.1007/s00330-023-10105-4
    By:
    • Ohno, Yoshiharu;
    • Yui, Masao;
    • Yamamoto, Kaori;
    • Ikedo, Masato;
    • Oshima, Yuka;
    • Hamabuchi, Nayu;
    • Hanamatsu, Satomu;
    • Nagata, Hiroyuki;
    • Ueda, Takahiro;
    • Ikeda, Hirotaka;
    • Takenaka, Daisuke;
    • Yoshikawa, Takeshi;
    • Ozawa, Yoshiyuki;
    • Toyama, Hiroshi
    Publication type:
    Article
    2

    Comparison of lung CT number and airway dimension evaluation capabilities of ultra-high-resolution CT, using different scan modes and reconstruction methods including deep learning reconstruction, with those of multi-detector CT in a QIBA phantom study.

    Published in:
    European Radiology, 2023, v. 33, n. 1, p. 368, doi. 10.1007/s00330-022-08983-1
    By:
    • Ohno, Yoshiharu;
    • Akino, Naruomi;
    • Fujisawa, Yasuko;
    • Kimata, Hirona;
    • Ito, Yuya;
    • Fujii, Kenji;
    • Kataoka, Yumi;
    • Ida, Yoshihiro;
    • Oshima, Yuka;
    • Hamabuchi, Nayu;
    • Shigemura, Chika;
    • Watanabe, Ayumi;
    • Obama, Yuki;
    • Hanamatsu, Satomu;
    • Ueda, Takahiro;
    • Ikeda, Hirotaka;
    • Murayama, Kazuhiro;
    • Toyama, Hiroshi
    Publication type:
    Article
    3

    Comparison of utility of deep learning reconstruction on 3D MRCPs obtained with three different k-space data acquisitions in patients with IPMN.

    Published in:
    European Radiology, 2022, v. 32, n. 10, p. 6658, doi. 10.1007/s00330-022-08877-2
    By:
    • Matsuyama, Takahiro;
    • Ohno, Yoshiharu;
    • Yamamoto, Kaori;
    • Ikedo, Masato;
    • Yui, Masao;
    • Furuta, Minami;
    • Fujisawa, Reina;
    • Hanamatsu, Satomu;
    • Nagata, Hiroyuki;
    • Ueda, Takahiro;
    • Ikeda, Hirotaka;
    • Takeda, Saki;
    • Iwase, Akiyoshi;
    • Fukuba, Takashi;
    • Akamatsu, Hokuto;
    • Hanaoka, Ryota;
    • Kato, Ryoichi;
    • Murayama, Kazuhiro;
    • Toyama, Hiroshi
    Publication type:
    Article
    4
    5

    Newly developed artificial intelligence algorithm for COVID-19 pneumonia: utility of quantitative CT texture analysis for prediction of favipiravir treatment effect.

    Published in:
    Japanese Journal of Radiology, 2022, v. 40, n. 8, p. 800, doi. 10.1007/s11604-022-01270-5
    By:
    • Ohno, Yoshiharu;
    • Aoyagi, Kota;
    • Arakita, Kazumasa;
    • Doi, Yohei;
    • Kondo, Masashi;
    • Banno, Sumi;
    • Kasahara, Kei;
    • Ogawa, Taku;
    • Kato, Hideaki;
    • Hase, Ryota;
    • Kashizaki, Fumihiro;
    • Nishi, Koichi;
    • Kamio, Tadashi;
    • Mitamura, Keiko;
    • Ikeda, Nobuhiro;
    • Nakagawa, Atsushi;
    • Fujisawa, Yasuko;
    • Taniguchi, Akira;
    • Ikeda, Hirotaka;
    • Hattori, Hidekazu
    Publication type:
    Article
    6
    7
    8

    Deep Learning Reconstruction for DWIs by EPI and FASE Sequences for Head and Neck Tumors.

    Published in:
    Cancers, 2024, v. 16, n. 9, p. 1714, doi. 10.3390/cancers16091714
    By:
    • Ikeda, Hirotaka;
    • Ohno, Yoshiharu;
    • Yamamoto, Kaori;
    • Murayama, Kazuhiro;
    • Ikedo, Masato;
    • Yui, Masao;
    • Kumazawa, Yunosuke;
    • Shimamura, Yurika;
    • Takagi, Yui;
    • Nakagaki, Yuhei;
    • Hanamatsu, Satomu;
    • Obama, Yuki;
    • Ueda, Takahiro;
    • Nagata, Hiroyuki;
    • Ozawa, Yoshiyuki;
    • Iwase, Akiyoshi;
    • Toyama, Hiroshi
    Publication type:
    Article
    9
    10
    11

    Computed DWI MRI Results in Superior Capability for N‐Stage Assessment of Non‐Small Cell Lung Cancer Than That of Actual DWI, STIR Imaging, and FDG‐PET/CT.

    Published in:
    Journal of Magnetic Resonance Imaging, 2023, v. 57, n. 1, p. 259, doi. 10.1002/jmri.28288
    By:
    • Ohno, Yoshiharu;
    • Yui, Masao;
    • Takenaka, Daisuke;
    • Yoshikawa, Takeshi;
    • Koyama, Hisanobu;
    • Kassai, Yoshimori;
    • Yamamoto, Kaori;
    • Oshima, Yuka;
    • Hamabuchi, Nayu;
    • Hanamatsu, Satomu;
    • Obama, Yuki;
    • Ueda, Takahiro;
    • Ikeda, Hirotaka;
    • Hattori, Hidekazu;
    • Murayama, Kazuhiro;
    • Toyama, Hiroshi
    Publication type:
    Article
    12

    Deep Learning Reconstruction to Improve the Quality of MR Imaging: Evaluating the Best Sequence for T-category Assessment in Non-small Cell Lung Cancer Patients.

    Published in:
    Magnetic Resonance in Medical Sciences, 2024, v. 23, n. 4, p. 487, doi. 10.2463/mrms.mp.2023-0068
    By:
    • Daisuke Takenaka;
    • Yoshiyuki Ozawa;
    • Kaori Yamamoto;
    • Maiko Shinohara;
    • Masato Ikedo;
    • Masao Yui;
    • Yuka Oshima;
    • Nayu Hamabuchi;
    • Hiroyuki Nagata;
    • Takahiro Ueda;
    • Hirotaka Ikeda;
    • Akiyoshi Iwase;
    • Takeshi Yoshikawa;
    • Hiroshi Toyama;
    • Yoshiharu Ohno
    Publication type:
    Article
    13

    State-of-the-art MR Imaging for Thoracic Diseases.

    Published in:
    Magnetic Resonance in Medical Sciences, 2022, v. 21, n. 1, p. 212, doi. 10.2463/mrms.rev.2020-0184
    By:
    • Yumi Tanaka;
    • Yoshiharu Ohno;
    • Satomu Hanamatsu;
    • Yuki Obama;
    • Takahiro Ueda;
    • Hirotaka Ikeda;
    • Akiyoshi Iwase;
    • Takashi Fukuba;
    • Hidekazu Hattori;
    • Kazuhiro Murayama;
    • Takeshi Yoshikawa;
    • Daisuke Takenaka;
    • Hisanobu Koyama;
    • Hiroshi Toyama
    Publication type:
    Article
    14
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    18

    Overview of MRI for pulmonary functional imaging.

    Published in:
    British Journal of Radiology, 2022, v. 95, n. 1132, p. 1, doi. 10.1259/bjr.20201053
    By:
    • Ohno, Yoshiharu;
    • Hanamatsu, Satomu;
    • Obama, Yuki;
    • Ueda, Takahiro;
    • Ikeda, Hirotaka;
    • Hattori, Hidekazu;
    • Murayama, Kazuhiro;
    • Toyama, Hiroshi
    Publication type:
    Article
    19