AIMC Topic: 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...
Tomography, X-Ray Computed Sensitivity and Specificity Lung Computers Humans Retrospective Studies Solitary Pulmonary Nodule Deep Learning Early Detection of Cancer Lung Neoplasms Radiographic Image Interpretation, Computer-Assisted Multiple Pulmonary Nodules
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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 Radiographic Image Interpretation, Computer-Assisted Ascites Calcium Algorithms Humans Tomography, X-Ray Computed Artificial Intelligence Iodine
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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...
Image Processing, Computer-Assisted Abdomen Obesity Tomography, X-Ray Computed Deep Learning Pelvis Radiographic Image Interpretation, Computer-Assisted Radiation Dosage Humans 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...
Humans Algorithms Retrospective Studies Radiation Dosage Computed Tomography Angiography Moyamoya Disease Deep Learning Radiographic Image Interpretation, Computer-Assisted
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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.
Humans Radiologists Radiographic Image Interpretation, Computer-Assisted Algorithms Retrospective Studies Tomography, X-Ray Computed Deep Learning Bone Neoplasms
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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.
Humans Retrospective Studies Tomography, X-Ray Computed Radiographic Image Interpretation, Computer-Assisted Signal-To-Noise Ratio Deep Learning Radiography, Dual-Energy Scanned Projection Liver Neoplasms Image Processing, 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.
Radiographic Image Interpretation, Computer-Assisted Pulmonary Emphysema Radiation Dosage Emphysema Retrospective Studies Tomography, X-Ray Computed Deep Learning Humans Algorithms
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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...
Radiation Dosage Urolithiasis Urinary Calculi Tomography, X-Ray Computed Deep Learning Radiographic Image Interpretation, Computer-Assisted Humans Algorithms
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Utilizing Synthetic Nodules for Improving Nodule Detection in Chest Radiographs.

Journal of digital imaging Mar 18, 2022
Algorithms that automatically identify nodular patterns in chest X-ray (CXR) images could benefit radiologists by reducing reading time and improving accuracy. A promising approach is to use deep learning, where a deep neural network (DNN) is trained...
Humans Neural Networks, Computer Algorithms Radiography, Thoracic Radiography Radiographic Image Interpretation, Computer-Assisted
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Unenhanced abdominal low-dose CT reconstructed with deep learning-based image reconstruction: image quality and anatomical structure depiction.

Japanese journal of radiology Mar 14, 2022
PURPOSE: To evaluate the utility of deep learning-based image reconstruction (DLIR) algorithm in unenhanced abdominal low-dose CT (LDCT).
Tomography, X-Ray Computed Deep Learning Humans Radiographic Image Interpretation, Computer-Assisted Image Processing, Computer-Assisted Algorithms Radiation Dosage Signal-To-Noise Ratio
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