[1]. Simultaneous Visualization of the Carotid and Subclavian Arteries Using Non-Contrast-Enhanced MR Angiography With a 3D Fast Field Echo Sequence and Time-Spatial Labeling Inversion pulse:A Comparison With 3D Time-of-Fight MR Angiography
Journal of magnetic resonance imaging : JMRI （2025年） [査読] 有
[DOI] [2]. RadVLM: A Multitask Conversational Vision-Language Model for Radiology
arXiv （2025年） [査読] 無
[3]. 当院における,オープンアーキテクチャによる,マルチベンダー画像システム(VNA)の取り組み
INNERVISION (株)インナービジョン [巻]39 [号]3付録 [頁]37 -37 （2024年） [査読] 無
[4]. Radiology-Aware Model-Based Evaluation Metric for Report Generation
arXiv （2023年） [査読] 無
[5]. AI画像解析によるがんのフォローアップ診断支援
INNERVISION (株)インナービジョン [巻]38 [号]6付録 [頁]6 -7 （2023年） [査読] 無
[6]. UF-DCE MRI画像を用いた腫瘍血管の長さの定量評価および乳がんサブタイプの関連性の検討[大会長賞記録]
日本磁気共鳴医学会雑誌(Web) [巻]43 [号]2 （2023年） [査読] 有
[7]. Reproducibility assessment of uptake on dedicated breast PET for noise discrimination
Annals of Nuclear Medicine Springer Science and Business Media LLC [巻]37 [号]2 [頁]121 -130 （2022年） [査読] 有
[DOI] [8]. 症例報告を対象とした固有表現抽出手法の比較
医療情報学連合大会論文集 (一社)日本医療情報学会 [巻]42回 [頁]1155 -1158 （2022年） [査読] 有
[9]. Super-resolution application of generative adversarial network on brain time-of-flight MR angiography: image quality and diagnostic utility evaluation
European Radiology Springer Science and Business Media LLC [巻]33 [号]2 [頁]936 -946 （2022年） [査読] 有
[DOI] [10]. Peritumoral radiomics features on preoperative thin-slice CT images can predict the spread through air spaces of lung adenocarcinoma.
Scientific reports [巻]12 [号]1 [頁]10323 -10323 （2022年） [査読] 有
[DOI] [11]. Risk Stratification for Pregnancies Diagnosed With Fetal Growth Restriction Based on Placental MRI.
Journal of magnetic resonance imaging : JMRI [巻]56 [号]6 [頁]1650 -1658 （2022年） [査読] 有
[DOI] [12]. Neuroimaging at 7 Tesla: a pictorial narrative review.
Quantitative imaging in medicine and surgery [巻]12 [号]6 [頁]3406 -3435 （2022年） [査読] 有
[DOI] [13]. Approach for Named Entity Recognition and Case Identification Implemented by ZuKyo-JA Sub-team at the NTCIR-16 Real-MedNLP Task
Proceedings of NTCIR-16 NTCIR 16 （2022年） [査読] 有
[14]. Leveraging Token-Based Concept Information and Data Augmentation in Few-Resource NER: ZuKyo-EN at the NTCIR-16 Real-MedNLP task
Proceedings of NTCIR-16 [巻]- [頁]316 -321 （2022年） [査読] 有
[15]. Deep learning-based algorithm improved radiologists' performance in bone metastases detection on CT.
European radiology [巻]32 [号]11 [頁]7976 -7987 （2022年） [査読] 有
[DOI] [16]. Picked-up Knowledge from Foreign Journals 女性骨盤MRI の最適化
画像診断 学研メディカル秀潤社 [巻]42 [号]5 [頁]450 -452 （2022年） [査読] 無
[DOI] [17]. 圧縮センシングを用いた腹部ダイナミックMRIの高速撮像
計算数理工学レビュー = JASCOME reviews : 日本計算数理工学会誌 / 日本計算数理工学会 編 東京 : 日本計算数理工学会 [巻]2022 [号]1 [頁]13 -20 （2022年） [査読] 無
[18]. Insertable inductively coupled volumetric coils for MR microscopy in a human 7T MR system.
Magnetic resonance in medicine Wiley [巻]87 [号]3 [頁]1613 -1620 （2022年） [査読] 有
[DOI] [19]. Corrigendum to "Radiomic machine learning for pretreatment assessment of prognostic risk factors for endometrial cancer and its effects on radiologists' decisions of deep myometrial invasion" [Magnetic Resonance Imaging 85 (2022) 161-167].
Magnetic resonance imaging [巻]95 [頁]119 -120 （2022年） [査読] 有
[DOI] [20]. Radiomic machine learning for pretreatment assessment of prognostic risk factors for endometrial cancer and its effects on radiologists' decisions of deep myometrial invasion.
Magnetic resonance imaging [巻]85 [頁]161 -167 （2022年） [査読] 有
[DOI] [21]. Placental functional assessment and its relationship to adverse pregnancy outcome: comparison of intravoxel incoherent motion (IVIM) MRI, T2-relaxation time, and umbilical artery Doppler ultrasound.
Acta radiologica (Stockholm, Sweden : 1987) [巻]64 [号]1 [頁]2841851211060410 -2841851211060410 （2021年） [査読] 有
[DOI] [22]. Lung Cancer Segmentation With Transfer Learning: Usefulness of a Pretrained Model Constructed From an Artificial Dataset Generated Using a Generative Adversarial Network
Frontiers in Artificial Intelligence Frontiers Media SA [巻]4 [頁]694815 -694815 （2021年） [査読] 有
[DOI] [23]. Automatic segmentation of uterine endometrial cancer on multi-sequence MRI using a convolutional neural network.
Scientific reports [巻]11 [号]1 [頁]14440 -14440 （2021年） [査読] 有
[DOI] [24]. Evaluation of Weighted Diffusion Subtraction for Detection of Clinically Significant Prostate Cancer.
Journal of magnetic resonance imaging : JMRI [巻]54 [号]6 [頁]1979 -1988 （2021年） [査読] 有
[DOI] [25]. Free‐breathing abdominal T 1 mapping using an optimized MR fingerprinting sequence
NMR in Biomedicine Wiley [巻]34 [号]7 [頁]e4531 （2021年） [査読] 有
[DOI] [26]. Convolutional neural network for classifying primary liver cancer based on triple-phase CT and tumor marker information: a pilot study.
Japanese journal of radiology [巻]39 [号]7 [頁]690 -702 （2021年） [査読] 有
[DOI]