Canon CT RSNA Abstracts

Photon Counting CT


Zhan et al, First Results From A Prototype Full-size Photon Counting CT System : Counting And Spectral Imaging Performance At Clinical Dose Levels

Nomura et al, Quantitative image quality comparison between photon counting and conventional CT systems: noise, resolution and quantitative accuracy

Super Resolution DLR


Higaki et al, Super-resolution deep learning reconstruction at CT: A phantom study for coronary CT angiography

Higaki et al, Various applications of deep learning-based reconstruction for CT: Denoise, Dual-energy CT, and super-resolution

Tatsugami et al, Improvement of spatial resolution by using super-resolution deep learning reconstruction at coronary CT angiography

Chen et al, Super Resolution Deep Learning Reconstruction Cardiac CT Angiography Image Quality

Boedeker et al, Three-Dimensional Super High Resolution Deep Learning Reconstruction Algorithm: Physics Performance Evaluation

Boedeker et al, Noise Properties And Low Contrast False Positive And False Negative Assessment Of A Super Resolution Deep Learning Reconstruction Algorithm Trained With Data From A Commercial High Resolution CT System

Deep Learning Reconstruction


Murayama et al, Deep Learning Reconstruction Vs. Hybrid-type Iterative Reconstruction Vs. Model-based Iterative Reconstruction: Capability For Image Quality And Disease Depiction Improvements On Unenhanced Brain CT In Acute Ischemic Stroke Patients.

Brady et al, Validation Of Reduced Dose CT For Detection Of Lung Nodules In Children With Cancer

Oostveen et al, Technical Performance Of A Novel Dual-energy CT System With Deep Learning-based Dual Energy Reconstruction

Ultra-high Resolution CT + DLR


Boedeker et al, Physics Evaluation of a High Resolution Computed Tomography System with De-Noising Deep Learning Reconstruction vs Normal Resolution with Hybrid Iterative Reconstruction for Lung

Iwasawa et al, Improvement Diagnostic Performance On Fibrotic Hypersensitivity Using UHR-CT

Shigemura et al, Ultra-high Resolution And Area-detector CTs For Lung Density Evaluation: Capability For Radiation Dose Reduction With Two-types Of Iterative Reconstruction And Deep Learning Reconstruction At QIBA phantom study.

Murayama et al, Deep Learning Reconstruction Vs. Hybrid-type Reconstruction Vs. Model-based Iterative Reconstruction: Capability For Image Quality Improvements On Brain Contrast-enhanced CT Angiography For Ultra-high-resolution CT

Moriya et al, Deep Learning Reconstruction In Chest CT - Issues Considered From The Dose Reduction And Image Quality In Clinical Cases

Moriya et al, Low-dose Head CT Using Deep Learning Reconstruction: Comparison Of Gray-white Matter Differentiation With Normal-dose Head CT

Fujii et al, Evaluation of apparent noise and low contrast detectability on abdominal phantom CT images reconstructed with a new deep learning algorithm

Hori et al, Advantages of the Latest Deep Learning Reconstruction Algorithm in Ultra-High-Resolution CT for Pancreatic Cystic Neoplasms

Hori et al, Ultra-High-Resolution CT with 1024-Matrix using a Novel Deep Learning Reconstruction Technique: How to use it for Abdominal Imaging

Ultra-high Resolution CT


Moriya et al, Depiction Of Bone Microstructures Using Ultra-high Resolution CT

Iwasawa et al, Radiological-pathological Correlation in Nonspecific Interstitial Pneumonia: State-of-art Images by Ultra-high-resolution CT

Moriya et al, Peripheral Pulmonary Artery Imaging Using Ultra-high Resolution CT - A New Method Of Evaluating Vascularity In The Lung Field

Moriya et al, Three-dimensional Image Of Intralobular Structure By Ultra-high-resolution CT

Moriya et al, Demonstration Of Collateral Pathways To The Artery Of Adamkiewicz Using Ultra-highresolution CT Angiography

Boone et al, Utility Of High-resolution CT For The Detection And Characterization Of Stenotic Lesions: A Phantom Study Using Model Observers

CT General


Moriya et al, Estimating Respiratory Volume By Measuring Thoracic Volume - Analysis Performed Using Respiratory Dynamics CT Data

Moriya et al, Eye Lens Exposure Reduction Method During Head CT Scanning

Fujii et al, Comparison of the regression fits between organ doses determined by Monte Carlo simulation and dose metrics in adult chest-abdomen-pelvis CT examinations across CT scanners

Hori et al, Principles and Clinical Utility of a Novel Contrast Enhancement Boost Techniq ue for Abdominal CT

Hoyama et al, Proposal of optimal contrast method for pulmonary artery/vein separation imaging : How to accomplish faster 3D image construction, reduced contrast agent dose, and improved image quality Teaching

Zhao et al, Low-dose Dynamic Pulmonary CT Perfusion Using Only Two Volume Scans

Zhao et al, Quantification Of Perfusion Defect Distal To Pulmonary Embolism Using Computed Tomography Angiography: Validation In A Swine Model