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Takeshi Nakaura

Showing results (121-130 of 285) with videos related to

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Academic Radiology|September 20, 2024
Advances in spatial resolution and radiation dose reduction using super-resolution deep learning-based reconstruction for abdominal computed tomography: A phantom studyYoshinori Funama, Yasunori Nagayama, Daisuke Sakabe, et al.
Journal of the Neurological Sciences|November 13, 2019
Perfusion abnormality on three-dimensional arterial spin labeling in patients with acute encephalopathy with biphasic seizures and late reduced diffusionHiroyuki Uetani, Mika Kitajima, Takeshi Sugahara, et al.
Radiation Medicine|July 20, 2007
Optimal dose and injection duration (injection rate) of contrast material for depiction of hypervascular hepatocellular carcinomas by multidetector CTYumi Yanaga, Kazuo Awai, Yoshiharu Nakayama, et al.
Japanese Journal of Radiology|December 22, 2019
Prevalence of extracardiac findings in patients undergoing coronary computed tomography and additional low-dose whole-body computed tomographyMorikatsu Yoshida, Daisuke Utsunomiya, Taihei Inoue, et al.
Academic Radiology|November 29, 2025
Performance of State-of-the-Art Multimodal Large Language Models on an Image-Rich Radiology Board Examination: Comparison to Human ExamineesTakeshi Nakaura, Naoki Kobayashi, Takanori Masuda, et al.
European Journal of Radiology|December 25, 2025
Evaluation of DeepSeek-R1 and contemporary large language models on the radiology board examination: A milestone achieved as open-source model matches performance with closed-source modelTakeshi Nakaura, Naoki Kobayashi, Takanori Masuda, et al.
European Radiology|June 13, 2013
Novel connecting tube for saline chaser in contrast-enhanced CT: the effect of spiral flow of saline on contrast enhancementMasafumi Kidoh, Takeshi Nakaura, Kazuo Awai, et al.
Journal of the Neurological Sciences|December 24, 2019
An initial experience of machine learning based on multi-sequence texture parameters in magnetic resonance imaging to differentiate glioblastoma from brain metastasesMachiko Tateishi, Takeshi Nakaura, Mika Kitajima, et al.
European Radiology|August 22, 2025
Intra-axial primary brain tumor differentiation: comparing large language models on structured MRI reports vs. radiologists on imagesTakeshi Nakaura, Hiroyuki Uetani, Naofumi Yoshida, et al.
Academic Radiology|June 20, 2022
Performance of Machine Learning Methods Based on Multi-Sequence Textural Parameters Using Magnetic Resonance Imaging and Clinical Information to Differentiate Malignant and Benign Soft Tissue TumorsMasataka Nakagawa, Takeshi Nakaura, Naofumi Yoshida, et al.
Pageof 29

Showing results (121-130 of 285) with videos related to

Sort By:
Pageof 29
Academic Radiology|September 20, 2024
Advances in spatial resolution and radiation dose reduction using super-resolution deep learning-based reconstruction for abdominal computed tomography: A phantom studyYoshinori Funama, Yasunori Nagayama, Daisuke Sakabe, et al.
Journal of the Neurological Sciences|November 13, 2019
Perfusion abnormality on three-dimensional arterial spin labeling in patients with acute encephalopathy with biphasic seizures and late reduced diffusionHiroyuki Uetani, Mika Kitajima, Takeshi Sugahara, et al.
Radiation Medicine|July 20, 2007
Optimal dose and injection duration (injection rate) of contrast material for depiction of hypervascular hepatocellular carcinomas by multidetector CTYumi Yanaga, Kazuo Awai, Yoshiharu Nakayama, et al.
Japanese Journal of Radiology|December 22, 2019
Prevalence of extracardiac findings in patients undergoing coronary computed tomography and additional low-dose whole-body computed tomographyMorikatsu Yoshida, Daisuke Utsunomiya, Taihei Inoue, et al.
Academic Radiology|November 29, 2025
Performance of State-of-the-Art Multimodal Large Language Models on an Image-Rich Radiology Board Examination: Comparison to Human ExamineesTakeshi Nakaura, Naoki Kobayashi, Takanori Masuda, et al.
European Journal of Radiology|December 25, 2025
Evaluation of DeepSeek-R1 and contemporary large language models on the radiology board examination: A milestone achieved as open-source model matches performance with closed-source modelTakeshi Nakaura, Naoki Kobayashi, Takanori Masuda, et al.
European Radiology|June 13, 2013
Novel connecting tube for saline chaser in contrast-enhanced CT: the effect of spiral flow of saline on contrast enhancementMasafumi Kidoh, Takeshi Nakaura, Kazuo Awai, et al.
Journal of the Neurological Sciences|December 24, 2019
An initial experience of machine learning based on multi-sequence texture parameters in magnetic resonance imaging to differentiate glioblastoma from brain metastasesMachiko Tateishi, Takeshi Nakaura, Mika Kitajima, et al.
European Radiology|August 22, 2025
Intra-axial primary brain tumor differentiation: comparing large language models on structured MRI reports vs. radiologists on imagesTakeshi Nakaura, Hiroyuki Uetani, Naofumi Yoshida, et al.
Academic Radiology|June 20, 2022
Performance of Machine Learning Methods Based on Multi-Sequence Textural Parameters Using Magnetic Resonance Imaging and Clinical Information to Differentiate Malignant and Benign Soft Tissue TumorsMasataka Nakagawa, Takeshi Nakaura, Naofumi Yoshida, et al.
Pageof 29