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Kota Aoyagi

Three-way Comparison of Whole-Body MR, Coregistered Whole-Body FDG PET/MR, and Integrated Whole-Body FDG PET/CT Imaging: TNM and Stage Assessment Capability for Non–Small Cell Lung Cancer Patients
2015 · Yoshiharu Ohno, Hisanobu Koyama, et al. · Radiology · 75
Comparative evaluation of newly developed model-based and commercially available hybrid-type iterative reconstruction methods and filter back projection method in terms of accuracy of computer-aided volumetry (CADv) for low-dose CT protocols in phantom study
2016 · Yoshiharu Ohno, Atsushi Yaguchi, et al. · European Journal of Radiology · 53
Differentiation of Benign from Malignant Pulmonary Nodules by Using a Convolutional Neural Network to Determine Volume Change at Chest CT
2020 · Yoshiharu Ohno, Kota Aoyagi, et al. · Radiology · 34
Machine learning for lung CT texture analysis: Improvement of inter-observer agreement for radiological finding classification in patients with pulmonary diseases
2020 · Yoshiharu Ohno, Kota Aoyagi, et al. · European Journal of Radiology · 32
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Comparison of Diagnostic Accuracy for TNM Stage Among Whole-Body MRI and Coregistered PET/MRI Using 1.5-T and 3-T MRI Systems and Integrated PET/CT for Non–Small Cell Lung Cancer
2020 · Yoshiharu Ohno, Yoshikawa Takeshi, et al. · American Journal of Roentgenology · 29
Small Cell Lung Cancer Staging: Prospective Comparison of Conventional Staging Tests, FDG PET/CT, Whole-Body MRI, and Coregistered FDG PET/MRI
2021 · Yoshiharu Ohno, Takeshi Yoshikawa, et al. · American Journal of Roentgenology · 27
Whole-Body MRI: Comparison of Its Capability for TNM Staging of Malignant Pleural Mesothelioma With That of Coregistered PET/MRI, Integrated FDG PET/CT, and Conventional Imaging
2018 · Yoshiharu Ohno, Masao Yui, et al. · American Journal of Roentgenology · 24
Newly developed artificial intelligence algorithm for COVID-19 pneumonia: utility of quantitative CT texture analysis for prediction of favipiravir treatment effect
2022 · Yoshiharu Ohno, Kota Aoyagi, et al. · Japanese Journal of Radiology · 22
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Diagnostic performance of different imaging modalities in the assessment of distant metastasis and local recurrence of tumor in patients with non‐small cell lung cancer
2017 · Yoshiharu Ohno, Takeshi Yoshikawa, et al. · Journal of Magnetic Resonance Imaging · 22
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Comparison of Interobserver Agreement and Diagnostic Accuracy for IASLC/ITMIG Thymic Epithelial Tumor Staging Among Co-registered FDG-PET/MRI, Whole-body MRI, Integrated FDG-PET/CT, and Conventional Imaging Examination with and without Contrast Media Administrations
2018 · Yoshiharu Ohno, Yuji Kishida, et al. · Academic Radiology · 20
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[Usefulness of 18F-FDG PET for diagnosis of cardiac sarcoidosis].
1999 · W Okumura, T Iwasaki, et al. · PubMed · 20
Automated chest CT three-dimensional quantification of body composition: adipose tissue and paravertebral muscle
2024 · Akinori Hata, Yohei Muraguchi, et al. · Scientific Reports · 17
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Machine learning for lung texture analysis on thin-section CT: Capability for assessments of disease severity and therapeutic effect for connective tissue disease patients in comparison with expert panel evaluations
2021 · Yoshiharu Ohno, Kota Aoyagi, et al. · Acta Radiologica · 16
Comparison of computer-aided detection (CADe) capability for pulmonary nodules among standard-, reduced- and ultra-low-dose CTs with and without hybrid type iterative reconstruction technique
2018 · Yoshiharu Ohno, Kota Aoyagi, et al. · European Journal of Radiology · 16
Automated Interstitial Lung Abnormality Probability Prediction at CT: A Stepwise Machine Learning Approach in the Boston Lung Cancer Study
2024 · Akinori Hata, Kota Aoyagi, et al. · Radiology · 12
3D fully convolutional network-based segmentation of lung nodules in CT images with a clinically inspired data synthesis method
2019 · Atsushi Yaguchi, Kota Aoyagi, et al. · SPIE Medical Imaging: Computer-Aided Diagnosis · 8
Lung stress mapping: an innovative technology to visualize the hidden risk of ventilator-induced lung injury
2026 · Takashi Maezawa, Taiki Hoshino, et al. · American Journal of Respiratory and Critical Care Medicine · 5
Semi-automated segmentation of solid and GGO nodules in lung CT images using vessel-likelihood derived from local foreground structure
2015 · Atsushi Yaguchi, Tomoya Okazaki, et al. · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 5
Medical Imaging Apparatus, Ultrasonic Imaging Apparatus, Magnetic Resonance Imaging Apparatus, Medical Image Processing Apparatus, and Medical Image Processing Method
2013 · Kota Aoyagi · The Journal of the Acoustical Society of America · 4
Machine learning-based computer-aided simple triage (CAST) for COVID-19 pneumonia as compared with triage by board-certified chest radiologists
2023 · Yoshiharu Ohno, Takatoshi Aoki, et al. · Japanese Journal of Radiology · 3
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Automated interstitial lung abnormalities detection at CT: external validation and potential recognition of traction bronchiectasis/bronchiolectasis
2025 · Yusei Nakamura, Taiki Fukuda, et al. · Japanese Journal of Radiology · 1
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Response to RMED-D-22–00,258.R1
2022 · Yoshiharu Ohno, Kota Aoyagi, et al. · Japanese Journal of Radiology · 1
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Prognostic value of AI-derived probability of interstitial lung abnormalities and interstitial lung disease in patients with esophageal cancer
2026 · Akinori Hata, Masahiro Yanagawa, et al. · Japanese Journal of Radiology
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Erratum to “Computer-aided volumetry with convolutional neural network: Application in the evaluation of invasiveness of lung adenocarcinoma on high-definition CT images” [Eur. J. Radiol. Artif. Intell. 7 (2026) 100103]
2026 · Yoshiyuki Ozawa, Kota Aoyagi, et al. · European Journal of Radiology Artificial Intelligence
Computer-aided volumetry with convolutional neural network: Application in the evaluation of invasiveness of lung adenocarcinoma on high-definition CT images
2026 · Yoshiyuki Ozawa, Kota Aoyagi, et al. · European Journal of Radiology Artificial Intelligence
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Works count: 30
Citation count: 446
H-index: 14
I10-index: 15
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