AIMC Topic: Radiographic Image Interpretation, Computer-Assisted

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Can convolutional neural networks identify external carotid artery calcifications?

Oral surgery, oral medicine, oral pathology and oral radiology Apr 20, 2023
OBJECTIVE: We developed and evaluated the accuracy and reliability of a convolutional neural network (CNN) in detecting external carotid artery calcifications (ECACs) in cone beam computed tomography scans.
Middle Aged Cone-Beam Computed Tomography Calcinosis Radiographic Image Interpretation, Computer-Assisted Reproducibility of Results Aged Male Vascular Calcification Carotid Artery, External Carotid Artery Diseases Humans Neural Networks, Computer Female
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Evaluation of Image Quality and Detectability of Deep Learning Image Reconstruction (DLIR) Algorithm in Single- and Dual-energy CT.

Journal of digital imaging Apr 18, 2023
This study is aimed to evaluate effects of deep learning image reconstruction (DLIR) on image quality in single-energy CT (SECT) and dual-energy CT (DECT), in reference to adaptive statistical iterative reconstruction-V (ASIR-V). The Gammex 464 phant...
Humans Algorithms Tomography, X-Ray Computed Deep Learning Phantoms, Imaging Image Processing, Computer-Assisted Radiographic Image Interpretation, Computer-Assisted Radiation Dosage
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A deep learning model based on contrast-enhanced computed tomography for differential diagnosis of gallbladder carcinoma.

Hepatobiliary & pancreatic diseases international : HBPD INT Apr 11, 2023
BACKGROUND: Gallbladder carcinoma (GBC) is highly malignant, and its early diagnosis remains difficult. This study aimed to develop a deep learning model based on contrast-enhanced computed tomography (CT) images to assist radiologists in identifying...
Aged Adult Male Middle Aged Tomography, X-Ray Computed Female Humans Reproducibility of Results Retrospective Studies Predictive Value of Tests Deep Learning Radiographic Image Interpretation, Computer-Assisted Support Vector Machine Gallbladder Neoplasms Contrast Media Cholecystectomy Diagnosis, Differential
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Assessing the Effects of Deep Learning Reconstruction on Abdominal CT Without Arm Elevation.

Canadian Association of Radiologists journal = Journal l'Association canadienne des radiologistes Apr 11, 2023
To evaluate the effects of deep learning reconstruction (DLR) on image quality of abdominal computed tomography (CT) in patients without arm elevation compared with hybrid-iterative reconstruction (Hybrid-IR) and filtered back projection (FBP). In ...
Tomography, X-Ray Computed Deep Learning Radiographic Image Interpretation, Computer-Assisted Arm Radiation Dosage Humans Algorithms Retrospective Studies
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Developing deep learning methods for classification of teeth in dental panoramic radiography.

Oral surgery, oral medicine, oral pathology and oral radiology Mar 30, 2023
OBJECTIVES: We aimed to develop an artificial intelligence-based clinical dental decision-support system using deep-learning methods to reduce diagnostic interpretation error and time and increase the effectiveness of dental treatment and classificat...
Radiography, Panoramic Radiographic Image Interpretation, Computer-Assisted Tooth, Impacted Female Humans Male Neural Networks, Computer Deep Learning Retrospective Studies Decision Support Systems, Clinical
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Improving lesion conspicuity in abdominal dual-energy CT with deep learning image reconstruction: a prospective study with five readers.

European radiology Mar 28, 2023
OBJECTIVES: To evaluate image quality, diagnostic acceptability, and lesion conspicuity in abdominal dual-energy CT (DECT) using deep learning image reconstruction (DLIR) compared to those using adaptive statistical iterative reconstruction-V (Asir-V...
Humans Image Processing, Computer-Assisted Algorithms Prospective Studies Radiographic Image Interpretation, Computer-Assisted Tomography, X-Ray Computed Radiation Dosage Deep Learning
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A Characterization of Deep Learning Reconstruction Applied to Dual-Energy Computed Tomography Monochromatic and Material Basis Images.

Journal of computer assisted tomography Mar 22, 2023
OBJECTIVE: Advancements in computed tomography (CT) reconstruction have enabled image quality improvements and dose reductions. Previous advancements have included iterative and model-based reconstruction. The latest image reconstruction advancement ...
Radiation Dosage Phantoms, Imaging Image Processing, Computer-Assisted Humans Radiographic Image Interpretation, Computer-Assisted Algorithms Quality Improvement Tomography, X-Ray Computed Deep Learning
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Application of Deep Learning-Based Denoising Technique for Radiation Dose Reduction in Dynamic Abdominal CT: Comparison with Standard-Dose CT Using Hybrid Iterative Reconstruction Method.

Journal of digital imaging Mar 21, 2023
The purpose is to evaluate whether deep learning-based denoising (DLD) algorithm provides sufficient image quality for abdominal computed tomography (CT) with a 30% reduction in radiation dose, compared to standard-dose CT reconstructed with conventi...
Radiographic Image Interpretation, Computer-Assisted Radiation Dosage Drug Tapering Algorithms Tomography, X-Ray Computed Deep Learning Humans
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Low dose of contrast agent and low radiation liver computed tomography with deep-learning-based contrast boosting model in participants at high-risk for hepatocellular carcinoma: prospective, randomized, double-blind study.

European radiology Mar 18, 2023
OBJECTIVE: To investigate the image quality and lesion conspicuity of a deep-learning-based contrast-boosting (DL-CB) algorithm on double-low-dose (DLD) CT of simultaneous reduction of radiation and contrast doses in participants at high-risk for hep...
Algorithms Prospective Studies Tomography, X-Ray Computed Deep Learning Liver Neoplasms Carcinoma, Hepatocellular Contrast Media Humans Double-Blind Method Radiographic Image Interpretation, Computer-Assisted Radiation Dosage
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Deep Learning Prediction for Distal Aortic Remodeling After Thoracic Endovascular Aortic Repair in Stanford Type B Aortic Dissection.

Journal of endovascular therapy : an official journal of the International Society of Endovascular Specialists Mar 16, 2023
PURPOSE: This study aimed to develop a deep learning model for predicting distal aortic remodeling after proximal thoracic endovascular aortic repair (TEVAR) in patients with Stanford type B aortic dissection (TBAD) using computed tomography angiogra...
Aortic Dissection Endovascular Aneurysm Repair Risk Factors Aortic Aneurysm, Thoracic Vascular Remodeling Aged Blood Vessel Prosthesis Implantation Humans Computed Tomography Angiography Adult Endovascular Procedures Decision Support Techniques Middle Aged Aortography Predictive Value of Tests Male Retrospective Studies Deep Learning Radiographic Image Interpretation, Computer-Assisted Female Time Factors Aorta, Thoracic Treatment Outcome
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