Shota Ichikawa
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View article: Development and Validation of Transformer- and Convolutional Neural Network-Based Deep Learning Models to Predict Curve Progression in Adolescent Idiopathic Scoliosis
Development and Validation of Transformer- and Convolutional Neural Network-Based Deep Learning Models to Predict Curve Progression in Adolescent Idiopathic Scoliosis Open
Background/Objectives: The clinical management of adolescent idiopathic scoliosis (AIS) is hindered by the inability to accurately predict curve progression. Although skeletal maturity and the initial Cobb angle are established predictors …
View article: The efficacy of velar adhesion in unilateral cleft lip and palate patients: Cleft width and otitis media with effusion
The efficacy of velar adhesion in unilateral cleft lip and palate patients: Cleft width and otitis media with effusion Open
Background Cleft lip and palate (CLP) is one of the most common congenital anomalies, affecting ~1 in 700 births worldwide. Patients with CLP often experience functional impairments due to the cleft palate, particularly related to feeding …
View article: Improving Cerebrovascular Imaging with Deep Learning: Semantic Segmentation for Time-of-Flight Magnetic Resonance Angiography Maximum Intensity Projection Image Enhancement
Improving Cerebrovascular Imaging with Deep Learning: Semantic Segmentation for Time-of-Flight Magnetic Resonance Angiography Maximum Intensity Projection Image Enhancement Open
Magnetic Resonance Angiography (MRA) is widely used for cerebrovascular assessment, with Time-of-Flight (TOF) MRA being a common non-contrast imaging technique. However, maximum intensity projection (MIP) images generated from TOF-MRA ofte…
View article: Automatic Aortic Valve Extraction Using Deep Learning with Contrast-Enhanced Cardiac CT Images
Automatic Aortic Valve Extraction Using Deep Learning with Contrast-Enhanced Cardiac CT Images Open
Purpose: This study evaluates the use of deep learning techniques to automatically extract and delineate the aortic valve annulus region from contrast-enhanced cardiac CT images. Two approaches, namely, segmentation and object detection, w…
View article: Development of a Patient-Radiopharmaceutical Matching Verification System for Preventing Misadministration of Radioactive Drugs Using Mixed Reality:Development of a Deep-Learning Model Based on Video Acquired by a Camera Mounted on a Mixed Reality Device
Development of a Patient-Radiopharmaceutical Matching Verification System for Preventing Misadministration of Radioactive Drugs Using Mixed Reality:Development of a Deep-Learning Model Based on Video Acquired by a Camera Mounted on a Mixed Reality Device Open
View article: Machine learning‐based estimation of patient body weight from radiation dose metrics in computed tomography
Machine learning‐based estimation of patient body weight from radiation dose metrics in computed tomography Open
Purpose Currently, precise patient body weight (BW) at the time of diagnostic imaging cannot always be used for radiation dose management. Various methods have been explored to address this issue, including the application of deep learning…
View article: The Effectiveness of Semi-Supervised Learning Techniques in Identifying Calcifications in X-ray Mammography and the Impact of Different Classification Probabilities
The Effectiveness of Semi-Supervised Learning Techniques in Identifying Calcifications in X-ray Mammography and the Impact of Different Classification Probabilities Open
Identifying calcifications in mammograms is crucial for early breast cancer detection, and semi-supervised learning, which utilizes a small dataset for supervised learning combined with deep learning, is anticipated to be an effective appr…
View article: Development of a Method for Estimating the Angle of Lumbar Spine X-ray Images Using Deep Learning with Pseudo X-ray Images Generated from Computed Tomography
Development of a Method for Estimating the Angle of Lumbar Spine X-ray Images Using Deep Learning with Pseudo X-ray Images Generated from Computed Tomography Open
Background and Objectives: In lumbar spine radiography, the oblique view is frequently utilized to assess the presence of spondylolysis and the morphology of facet joints. It is crucial to instantly determine whether the oblique angle is a…
View article: Development of a Patient–Radiopharmaceutical Matching System Using Smartphone to Prevent Misadministration: Feasibility Study
Development of a Patient–Radiopharmaceutical Matching System Using Smartphone to Prevent Misadministration: Feasibility Study Open
放射性医薬品の誤投与は防ぐ必要がある。本研究では,スマートフォンを用いた誤投与防止のための患者–放射性医薬品照合システム開発を考案し,その要素技術である放射性医薬品の容器を識別する深層学習モデルを開発した。ResNet18の転移学習および10分割交差検証を実施した結果,15種類の放射性医薬品容器をすべて正確に分類できた。本研究により,提案システムの実現可能性が証明された。
View article: Accuracy of Effective Diameter and Water Equivalent Diameter Using Phantoms in Various CT Systems
Accuracy of Effective Diameter and Water Equivalent Diameter Using Phantoms in Various CT Systems Open
Although the ED did not show any dependence on the CT system, the accuracy of WED for fusion CT was low. We found that there are issues in the management of scanning data, including the upper limb.
View article: Development of a Mammography Calcification Detection Algorithm Using Deep Learning with Resolution-Preserved Image Patch Division
Development of a Mammography Calcification Detection Algorithm Using Deep Learning with Resolution-Preserved Image Patch Division Open
Convolutional neural networks (CNNs) in deep learning have input pixel limitations, which leads to lost information regarding microcalcification when mammography images are compressed. Segmenting images into patches retains the original re…
View article: Estimation of Left and Right Ventricular Ejection Fractions from cine-MRI Using 3D-CNN
Estimation of Left and Right Ventricular Ejection Fractions from cine-MRI Using 3D-CNN Open
Cardiac function indices must be calculated using tracing from short-axis images in cine-MRI. A 3D-CNN (convolutional neural network) that adds time series information to images can estimate cardiac function indices without tracing using i…
View article: Deep learning‐based body weight from scout images can be an alternative to actual body weight in CT radiation dose management
Deep learning‐based body weight from scout images can be an alternative to actual body weight in CT radiation dose management Open
Purpose Accurate body weight measurement is essential to promote computed tomography (CT) dose optimization; however, body weight cannot always be measured prior to CT examination, especially in the emergency setting. The aim of this study…
View article: Development of Chest X-ray Image Evaluation Software Using the Deep Learning Techniques
Development of Chest X-ray Image Evaluation Software Using the Deep Learning Techniques Open
Although the widespread use of digital imaging has enabled real-time image display, images in chest X-ray examinations can be confirmed by the radiologist’s eyes. Considering the development of deep learning (DL) technology, its applicatio…
View article: Acquisition time reduction in pediatric <sup>99m</sup>Tc‐DMSA planar imaging using deep learning
Acquisition time reduction in pediatric <sup>99m</sup>Tc‐DMSA planar imaging using deep learning Open
Purpose Given the potential risk of motion artifacts, acquisition time reduction is desirable in pediatric 99m Tc‐dimercaptosuccinic acid (DMSA) scintigraphy. The aim of this study was to evaluate the performance of predicted full‐acquisit…
View article: Acquisition time reduction in pediatric 99mTc-DMSA planar imaging using deep learning
Acquisition time reduction in pediatric 99mTc-DMSA planar imaging using deep learning Open
Background: Given the potential risk of motion artifacts, acquisition time reduction is desirable in pediatric 99mTc-dimercaptosuccinic acid (DMSA) scintigraphy. The purpose of this study was to assess the performance of predict…
View article: An artificial intelligence system for predicting body weight from chest radiographs
An artificial intelligence system for predicting body weight from chest radiographs Open
Background In the field of diagnostic radiology, radiation dose management, determination of the contrast-medium dose, or estimation of the specific absorption rate level require patients’ body weight. However, accurate body weight is not …
View article: A deep-learning method using computed tomography scout images for estimating patient body weight
A deep-learning method using computed tomography scout images for estimating patient body weight Open
View article: A Deep Learning Method for Estimating Patient Body Weight Using Computed Tomography Scout Images
A Deep Learning Method for Estimating Patient Body Weight Using Computed Tomography Scout Images Open
Body weight is an indispensable parameter for determination of the dose of contrast media, appropriate drug dosing, or management of radiation dose. However, we cannot always determine the accurate patient body weight at the time of comput…
View article: Scatter Radiation Intensities during Transforaminal Lumbar Interbody Fusion Using a Mobile C-arm System
Scatter Radiation Intensities during Transforaminal Lumbar Interbody Fusion Using a Mobile C-arm System Open
The purpose of this study was to measure the scatter radiation intensity during transforaminal lumbar interbody fusion using a mobile C-arm system (Arcadis Orbic 3D; Siemens) and minimize radiation exposure. Dosimetry was performed with an…
View article: Usefulness of Bayesian estimation algorithm for simulated low-dose cerebral computed tomography perfusion in patients with acute ischemic stroke
Usefulness of Bayesian estimation algorithm for simulated low-dose cerebral computed tomography perfusion in patients with acute ischemic stroke Open
Poster: ECR 2020 / C-07900 / Usefulness of Bayesian estimation algorithm for simulated low-dose cerebral computed tomography perfusion in patients with acute ischemic stroke by: S. Ichikawa , H. YAMAMOTO; Kurashiki/JP
View article: Detection of Fine Radiographic Progression in Finger Joint Space Narrowing Beyond Human Eyes: Phantom Experiment and Clinical Study with Rheumatoid Arthritis Patients
Detection of Fine Radiographic Progression in Finger Joint Space Narrowing Beyond Human Eyes: Phantom Experiment and Clinical Study with Rheumatoid Arthritis Patients Open
View article: Radiographic temporal subtraction analysis can detect finger joint space narrowing progression in rheumatoid arthritis with clinical low disease activity
Radiographic temporal subtraction analysis can detect finger joint space narrowing progression in rheumatoid arthritis with clinical low disease activity Open
Background Recent papers suggest that finger joints with positive synovial vascularity (SV) assessed by ultrasonography under clinical low disease activity (CLDA) in rheumatoid arthritis (RA) patients may cause joint space narrowing (JSN) …
View article: Cartilage quantification using contrast-enhanced MRI in the wrist of rheumatoid arthritis: cartilage loss is associated with bone marrow edema
Cartilage quantification using contrast-enhanced MRI in the wrist of rheumatoid arthritis: cartilage loss is associated with bone marrow edema Open
Objective: To quantify wrist cartilage using contrast MRI and compare with the extent of adjacent synovitis and bone marrow edema (BME) in patients with rheumatoid arthritis (RA). Methods: 18 patients with RA underwent post-contrast fat-su…
View article: Computer-Based Radiographic Quantification of Joint Space Narrowing Progression Using Sequential Hand Radiographs: Validation Study in Rheumatoid Arthritis Patients from Multiple Institutions
Computer-Based Radiographic Quantification of Joint Space Narrowing Progression Using Sequential Hand Radiographs: Validation Study in Rheumatoid Arthritis Patients from Multiple Institutions Open
View article: Semi-Automated Quantification of Finger Joint Space Narrowing Using Tomosynthesis in Patients with Rheumatoid Arthritis
Semi-Automated Quantification of Finger Joint Space Narrowing Using Tomosynthesis in Patients with Rheumatoid Arthritis Open
View article: Radiographic quantifications of joint space narrowing progression by computer-based approach using temporal subtraction in rheumatoid wrist
Radiographic quantifications of joint space narrowing progression by computer-based approach using temporal subtraction in rheumatoid wrist Open
The computer-based temporal subtraction method can detect the JSN progression in the wrist, which is the single most commonly involved site in RA.