Satomu Hanamatsu

发表

Compressed sensing and deep learning reconstruction for women's pelvic MRI denoising: Utility for improving image quality and examination time in routine clinical practice.

Y. Ohno, H. Toyama, M. Ikedo, 2020, European journal of radiology.

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

Y. Ohno, D. Takenaka, H. Toyama, 2022, Journal of magnetic resonance imaging : JMRI.

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

Y. Ohno, D. Takenaka, H. Toyama, 2021, Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine.

A Bayesian estimation method for cerebral blood flow measurement by area-detector CT perfusion imaging

M. Prokop, K. Katada, Y. Ohno, 2022, Neuroradiology.

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

Y. Ohno, H. Toyama, T. Ueda, 2022, European Radiology.

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

Y. Ohno, H. Toyama, R. Kato, 2022, European Radiology.

MR imaging for shoulder diseases: Effect of compressed sensing and deep learning reconstruction on examination time and imaging quality compared with that of parallel imaging.

Y. Ohno, H. Toyama, M. Ikedo, 2022, Magnetic resonance imaging.

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

Y. Ohno, H. Toyama, R. Kato, 2022, European Radiology.

Three-Dimensional Gradient-Echo–Based Amide Proton Transfer-Weighted Imaging of Brain Tumors: Comparison With Two-Dimensional Spin-Echo–Based Amide Proton Transfer-Weighted Imaging

Y. Ohno, H. Toyama, M. Ikedo, 2023, Journal of computer assisted tomography.

Overview of MRI for pulmonary functional imaging.

Y. Ohno, H. Toyama, Hidekazu Hattori, 2021, The British journal of radiology.

Deep Learning Reconstruction of Diffusion-weighted MRI Improves Image Quality for Prostatic Imaging.

Y. Ohno, H. Toyama, M. Ikedo, 2022, Radiology.

A Bayesian estimation method for cerebral blood flow measurement by area-detector CT perfusion imaging

M. Prokop, K. Katada, Y. Ohno, 2022, Neuroradiology.

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

Y. Ohno, D. Takenaka, H. Toyama, 2021, Acta radiologica.

Deep learning reconstruction for brain diffusion-weighted imaging: efficacy for image quality improvement, apparent diffusion coefficient assessment, and intravoxel incoherent motion evaluation in in vitro and in vivo studies.

Y. Ohno, H. Toyama, Kaori Yamamoto, 2023, Diagnostic and interventional radiology.

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

Y. Ohno, D. Takenaka, H. Toyama, 2021, Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine.

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

Y. Ohno, M. Ikedo, T. Ueda, 2024, Cancers.