A5064249421- Advanced MRI Techniques and Applications
- Medical Imaging and Analysis
- Advanced X-ray and CT Imaging
- Dental Radiography and Imaging
- Medical Imaging Techniques and Applications
- Radiomics and Machine Learning in Medical Imaging
- Material Dynamics and Properties
- Anatomy and Medical Technology
- Theoretical and Computational Physics
- Radiation Dose and Imaging
- Granular flow and fluidized beds
- Rheology and Fluid Dynamics Studies
- MRI in cancer diagnosis
- Electrostatics and Colloid Interactions
- Facial Nerve Paralysis Treatment and Research
- Cerebrovascular and Carotid Artery Diseases
- Cardiac Imaging and Diagnostics
- Advanced Image and Video Retrieval Techniques
- Fluid Dynamics and Vibration Analysis
- Nuclear Engineering Thermal-Hydraulics
- Facial Rejuvenation and Surgery Techniques
- Structural Response to Dynamic Loads
- Evacuation and Crowd Dynamics
- Radiology practices and education
- Lightning and Electromagnetic Phenomena
International University of Health and Welfare
2006-2024
Mita Hospital
2019-2023
Kitasato University Hospital
2023
Keio University
2023
RIKEN Center for Computational Science
2016-2019
The University of Tokyo
2005-2015
Sanno Medical Center
2012-2015
Konan Kosei Hospital
2015
Kyoto University
1973-2013
University of Debrecen
2012
Deep learning has been recognized as a paradigm-shifting tool in radiology. reconstruction (DLR) recently emerged technology used the image process of MRI, which is an essential procedure generating MR images. Denoising, first DLR application to be realized commercial MRI scanners, improves signal-to-noise ratio. When applied lower magnetic field-strength ratio can increased without extending imaging time, and quality comparable that higher-field-strength scanners. Shorter times decrease...
The purpose of this study was to evaluate whether deep learning reconstruction (DLR) improves the image quality intracranial magnetic resonance angiography (MRA) at 1.5 T.In retrospective study, MRA images 40 patients (21 males and 19 females; mean age, 65.8 ± 13.2 years) were reconstructed with without DLR technique (DLR non-DLR image, respectively). Quantitative analysis performed by placing regions interest on basilar artery cerebrospinal fluid in prepontine cistern. We calculated...
Abstract Purpose To evaluate whether deep learning reconstruction (DLR) accelerates the acquisition of 1.5-T magnetic resonance imaging (MRI) knee data without image deterioration. Materials and methods Twenty-one healthy volunteers underwent MRI right on a scanner. Proton-density-weighted images with one or four numbers signal averages (NSAs) were obtained via compressed sensing, DLR was applied to 1 NSA obtain 1NSA-DLR images. The 4NSA compared objectively (by deriving signal-to-noise...
The aim of this study was to investigate whether super-resolution deep learning reconstruction (SR-DLR) is superior conventional (DLR) with respect interobserver agreement in the evaluation neuroforaminal stenosis using 1.5T cervical spine MRI. This retrospective included 39 patients who underwent T2-weighted sagittal images were reconstructed SR-DLR and DLR. Three blinded radiologists independently evaluated terms degree stenosis, depictions vertebrae, spinal cord neural foramina,...
Abstract Purpose: To investigate age‐related differences, gender and age‐by‐gender interactions on the volumes of 18 neuroanatomical structures, with a large sample at single institution. Materials Methods: A total 861 normal subjects (mean age = 56.1 ± 9.8 years, range 24.0–84.8 years) were included in this study. All scanned 3.0 T. Measurement was performed FreeSurfer v. 4.5. Differences structures tested using analysis covariance intracranial volume‐normalized volume as dependent...
This study aimed to evaluate whether the image quality of 1.5T magnetic resonance imaging (MRI) knee is equal or higher than that 3T MRI by applying deep learning reconstruction (DLR).Proton density-weighted images right 27 healthy volunteers were obtained and scanners using similar parameters (21 for high resolution 6 normal image). Commercially available DLR was applied obtain 1.5T/DLR images. The compared subjectively visibility structures, noise, artifacts, overall diagnostic...
Abstract Background The superficial musculoaponeurotic system (SMAS) is an anatomical structure involved in the facial ageing process. We aimed to evaluate SMAS laxity using multi‐detector row computed tomography (MDCT) as a diagnostic tool, and analyse relationship between age. Methods Fifty‐seven female subjects (aged 21‐57 years) were enrolled study. divided into two age groups: one below mean (Group Y, 30 subjects) over it O, 27 subjects). Posture Change (PC)‐induced Laxity Index was...
We developed an online monitoring system to measure systolic blood pressure variation (SPV) and its down (dDown) up components, along with pulse (dPP). Using the system, we compared different cardiac preload indicators-such as stroke volume (SVV) corrected flow time (FTc)-along central venous pulmonary artery occlusion in mechanically-ventilated dogs during normovolemia, graded hypovolemia (-200 -350 mL), hypervolemia (+200 +350 mL). simultaneously measured these indicators global...
We study subcritical fracture driven by thermally activated damage accumulation in the framework of fiber bundle models. show that presence stress inhomogeneities, cracking results an anomalous size effect; i.e., average lifetime $⟨{t}_{f}⟩$ decreases as a power law system $⟨{t}_{f}⟩\ensuremath{\sim}{L}^{\ensuremath{-}z}$, where exponent $z$ depends on external load $\ensuremath{\sigma}$ and temperature $T$ form $z\ensuremath{\sim}f(\ensuremath{\sigma}/{T}^{3/2})$. propose modified Arrhenius...
Objective: We describe a new false positive (FP) reduction method based on surface features in our computerized detection system for lung nodules and evaluate the using clinical chest computed tomography (CT) scans. Methods: In method, nodule candidates are extracted volumetric curvature-based thresholding region growing. For various sizes of nodules, we adopt multiscale integration Hessian eigenvalues. each candidate, two calculated to differentiate FPs at vessel bifurcations. These fed...
Abstract The shape of a laminar, liquid jet emerging from round vertical tube into the atmosphere and total axial force exerted on filament at exit were investigated experimentally over wide range flow conditions. An integral invariant exact solution was used to check consistency between two kinds data. A new equation predict agreed moderately well with present experimental data as various previous results. key idea work is that knowledge will be very useful reasonably given condition by...
Based on a fiber bundle model we substantially extend the phase-transition analogy of thermally activated breakdown homogeneous materials. We show that competition breaking due to stress enhancement and thermal fluctuations leads an astonishing complexity phase space system: varying load temperature boundary emerges, separating Griffith-type regime abrupt failure analogous first-order transitions from disorder dominated fracture where spanning cluster cracks emerges. demonstrate is Kertész...
Anatomical landmarks are useful as the primitive anatomical knowledge for medical image understanding. In this study, we construct a unified framework automated detection of distributed within human body. Our includes following three elements; (1) initial candidate based on local appearance matching technique models built by PCA and generative learning, (2) false positive elimination using classifier ensembles trained MadaBoost, (3) final landmark set determination combination optimization...
Segmentation of vertebral bones in computed tomographic data is important as a first stage image-based radiological tasks. However, it challenging problem to segment an affected spine correctly. In this study, we propose new method segmentation thoracic and lumbar bodies from thin-slice images. Especially, focus on deformable model-based scheme confirm the feasibility clinical sets with various bone diseases, such metastases scoliosis. As application algorithm, virtual straightening...