AIMC Topic: Radiographic Image Interpretation, Computer-Assisted

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Feasibility of Deep Learning-Based Noise and Artifact Reduction in Coronal Reformation of Contrast-Enhanced Chest Computed Tomography.

Journal of computer assisted tomography May 20, 2022
PURPOSE: This study aimed to evaluate the feasibility of a deep learning method for imaging artifact and noise reduction in coronal reformation of contrast-enhanced chest computed tomography (CT).
Artifacts Algorithms Signal-To-Noise Ratio Tomography, X-Ray Computed Deep Learning Image Processing, Computer-Assisted Radiographic Image Interpretation, Computer-Assisted Feasibility Studies Humans
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Pulmonary emphysema quantification at low dose chest CT using Deep Learning image reconstruction.

European journal of radiology May 5, 2022
PURPOSE: Quantitative analysis of emphysema volume is affected by the radiation dose and the CT reconstruction technique. We aim to evaluate the influence of a commercially available deep learning image reconstruction algorithm (DLIR) on the quantifi...
Algorithms Retrospective Studies Tomography, X-Ray Computed Pulmonary Emphysema Humans Deep Learning Radiation Dosage Emphysema Image Processing, Computer-Assisted Radiographic Image Interpretation, Computer-Assisted
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Validation of a deep learning computer aided system for CT based lung nodule detection, classification, and growth rate estimation in a routine clinical population.

PloS one May 5, 2022
OBJECTIVE: In this study, we evaluated a commercially available computer assisted diagnosis system (CAD). The deep learning algorithm of the CAD was trained with a lung cancer screening cohort and developed for detection, classification, quantificati...
Lung Radiographic Image Interpretation, Computer-Assisted Deep Learning Humans Retrospective Studies Lung Neoplasms Multiple Pulmonary Nodules Computers Tomography, X-Ray Computed Solitary Pulmonary Nodule Sensitivity and Specificity Early Detection of Cancer
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Reconstruction Algorithm-Based CT Imaging for the Diagnosis of Hepatic Ascites.

Computational and mathematical methods in medicine May 4, 2022
The study was aimed at exploring the diagnostic value of artificial intelligence reconstruction algorithm combined with CT image parameters on hepatic ascites, expected to provide a reference for the etiological evaluation of clinical abdominal effus...
Water Calcium Algorithms Radiographic Image Interpretation, Computer-Assisted Tomography, X-Ray Computed Ascites Humans Iodine Artificial Intelligence
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Image Quality Evaluation in Dual-Energy CT of the Chest, Abdomen, and Pelvis in Obese Patients With Deep Learning Image Reconstruction.

Journal of computer assisted tomography Apr 27, 2022
OBJECTIVE: The aim of this study was to evaluate image quality in vascular and oncologic dual-energy computed tomography (CT) imaging studies performed with a deep learning (DL)-based image reconstruction algorithm in patients with body mass index of...
Radiographic Image Interpretation, Computer-Assisted Radiation Dosage Tomography, X-Ray Computed Deep Learning Image Processing, Computer-Assisted Abdomen Obesity Humans Pelvis Algorithms
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Evaluation of moyamoya disease in CT angiography using ultra-high-resolution computed tomography: Application of deep learning reconstruction.

European journal of radiology Apr 9, 2022
PURPOSE: The aim of this study was to examine the evaluation of ultra-high-resolution computed tomography angiography (UHR CTA) images in moyamoya disease (MMD) reconstructed with hybrid iterative reconstruction (Hybrid-IR), model-based iterative rec...
Deep Learning Radiographic Image Interpretation, Computer-Assisted Radiation Dosage Computed Tomography Angiography Moyamoya Disease Humans Algorithms Retrospective Studies
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Deep learning-based algorithm improved radiologists' performance in bone metastases detection on CT.

European radiology Apr 8, 2022
OBJECTIVES: To develop and evaluate a deep learning-based algorithm (DLA) for automatic detection of bone metastases on CT.
Deep Learning Bone Neoplasms Radiologists Algorithms Retrospective Studies Tomography, X-Ray Computed Radiographic Image Interpretation, Computer-Assisted Humans
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Deep learning-based image reconstruction of 40-keV virtual monoenergetic images of dual-energy CT for the assessment of hypoenhancing hepatic metastasis.

European radiology Apr 5, 2022
OBJECTIVES: To evaluate the diagnostic value of deep learning model (DLM) reconstructed dual-energy CT (DECT) low-keV virtual monoenergetic imaging (VMI) for assessing hypoenhancing hepatic metastases.
Tomography, X-Ray Computed Deep Learning Liver Neoplasms Humans Retrospective Studies Signal-To-Noise Ratio Radiography, Dual-Energy Scanned Projection Image Processing, Computer-Assisted Radiographic Image Interpretation, Computer-Assisted
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A Challenge for Emphysema Quantification Using a Deep Learning Algorithm With Low-dose Chest Computed Tomography.

Journal of thoracic imaging Apr 5, 2022
PURPOSE: We aimed to identify clinically relevant deep learning algorithms for emphysema quantification using low-dose chest computed tomography (LDCT) through an invitation-based competition.
Humans Algorithms Retrospective Studies Tomography, X-Ray Computed Deep Learning Emphysema Radiographic Image Interpretation, Computer-Assisted Pulmonary Emphysema Radiation Dosage
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Value of deep learning reconstruction at ultra-low-dose CT for evaluation of urolithiasis.

European radiology Mar 31, 2022
OBJECTIVES: To determine the diagnostic accuracy and image quality of ultra-low-dose computed tomography (ULDCT) with deep learning reconstruction (DLR) to evaluate patients with suspected urolithiasis, compared with ULDCT with hybrid iterative recon...
Urinary Calculi Radiographic Image Interpretation, Computer-Assisted Radiation Dosage Humans Urolithiasis Tomography, X-Ray Computed Algorithms Deep Learning
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