AIMC Topic: Radiographic Image Interpretation, Computer-Assisted

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Multiscale Attention Guided Network for COVID-19 Diagnosis Using Chest X-Ray Images.

IEEE journal of biomedical and health informatics May 11, 2021
Coronavirus disease 2019 (COVID-19) is one of the most destructive pandemic after millennium, forcing the world to tackle a health crisis. Automated lung infections classification using chest X-ray (CXR) images could strengthen diagnostic capability ...
Lung Deep Learning Radiographic Image Interpretation, Computer-Assisted Radiography, Thoracic Humans COVID-19 SARS-CoV-2
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Feasibility of high-resolution magnetic resonance imaging of the liver using deep learning reconstruction based on the deep learning denoising technique.

Magnetic resonance imaging May 7, 2021
PURPOSE: To evaluate the feasibility of High-resolution (HR) magnetic resonance imaging (MRI) of the liver using deep learning reconstruction (DLR) based on a deep learning denoising technique compared with standard-resolution (SR) imaging.
Signal-To-Noise Ratio Liver Radiographic Image Interpretation, Computer-Assisted Feasibility Studies Humans Retrospective Studies Deep Learning Magnetic Resonance Imaging Female Aged
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Assessment of an AI Aid in Detection of Adult Appendicular Skeletal Fractures by Emergency Physicians and Radiologists: A Multicenter Cross-sectional Diagnostic Study.

Radiology May 4, 2021
Background The interpretation of radiographs suffers from an ever-increasing workload in emergency and radiology departments, while missed fractures represent up to 80% of diagnostic errors in the emergency department. Purpose To assess the performan...
Humans Artificial Intelligence Physicians Aged Aged, 80 and over Young Adult Adult Retrospective Studies Female Reproducibility of Results Radiologists Radiographic Image Interpretation, Computer-Assisted Middle Aged Adolescent Fractures, Bone Emergency Service, Hospital Sensitivity and Specificity Cross-Sectional Studies Male
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AI-based Strategies to Reduce Workload in Breast Cancer Screening with Mammography and Tomosynthesis: A Retrospective Evaluation.

Radiology May 4, 2021
Background The workflow of breast cancer screening programs could be improved given the high workload and the high number of false-positive and false-negative assessments. Purpose To evaluate if using an artificial intelligence (AI) system could redu...
Radiographic Image Interpretation, Computer-Assisted Breast Workload Workflow Breast Neoplasms Middle Aged Humans Mammography Female Aged Artificial Intelligence Retrospective Studies
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Improvement of image quality for pancreatic cancer using deep learning-generated virtual monochromatic images: Comparison with single-energy computed tomography.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB) Apr 30, 2021
PURPOSE: To construct a deep convolutional neural network that generates virtual monochromatic images (VMIs) from single-energy computed tomography (SECT) images for improved pancreatic cancer imaging quality.
Signal-To-Noise Ratio Humans Deep Learning Retrospective Studies Physical Phenomena Pancreatic Neoplasms Tomography, X-Ray Computed Radiography, Dual-Energy Scanned Projection Radiographic Image Interpretation, Computer-Assisted
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Metal artefact reduction in the oral cavity using deep learning reconstruction algorithm in ultra-high-resolution computed tomography: a phantom study.

Dento maxillo facial radiology Apr 29, 2021
OBJECTIVES: This study aimed to improve the impact of the metal artefact reduction (MAR) algorithm for the oral cavity by assessing the effect of acquisition and reconstruction parameters on an ultra-high-resolution CT (UHRCT) scanner.
Mouth Reproducibility of Results Humans Radiation Dosage Deep Learning Artifacts Algorithms Phantoms, Imaging Radiographic Image Interpretation, Computer-Assisted Tomography, X-Ray Computed
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Comparison of image quality and lesion diagnosis in abdominopelvic unenhanced CT between reduced-dose CT using deep learning post-processing and standard-dose CT using iterative reconstruction: A prospective study.

European journal of radiology Apr 24, 2021
PURPOSE: To compare image quality and lesion diagnosis between reduced-dose abdominopelvic unenhanced computed tomography (CT) using deep learning (DL) post-processing and standard-dose CT using iterative reconstruction (IR).
Radiation Dosage Prospective Studies Humans Deep Learning Tomography, X-Ray Computed Algorithms China Radiographic Image Interpretation, Computer-Assisted
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Sinogram-based deep learning image reconstruction technique in abdominal CT: image quality considerations.

European radiology Apr 23, 2021
OBJECTIVES: To investigate the image quality and perception of a sinogram-based deep learning image reconstruction (DLIR) algorithm for single-energy abdominal CT compared to standard-of-care strength of ASIR-V.
Radiation Dosage Tomography, X-Ray Computed Deep Learning Image Processing, Computer-Assisted Radiographic Image Interpretation, Computer-Assisted Humans Algorithms Retrospective Studies
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Deep learning-based denoising algorithm in comparison to iterative reconstruction and filtered back projection: a 12-reader phantom study.

European radiology Apr 22, 2021
OBJECTIVES: (1) To compare low-contrast detectability of a deep learning-based denoising algorithm (DLA) with ADMIRE and FBP, and (2) to compare image quality parameters of DLA with those of reconstruction methods from two different CT vendors (ADMIR...
Phantoms, Imaging Deep Learning Radiographic Image Interpretation, Computer-Assisted Radiation Dosage Humans Algorithms Tomography, X-Ray Computed
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Deep learning to detect acute respiratory distress syndrome on chest radiographs: a retrospective study with external validation.

The Lancet. Digital health Apr 20, 2021
BACKGROUND: Acute respiratory distress syndrome (ARDS) is a common, but under-recognised, critical illness syndrome associated with high mortality. An important factor in its under-recognition is the variability in chest radiograph interpretation for...
Humans Neural Networks, Computer Female Aged Algorithms Retrospective Studies Area Under Curve Radiography Radiographic Image Interpretation, Computer-Assisted Hospitals Male Deep Learning Pleural Cavity Middle Aged United States Datasets as Topic Lung Pleural Diseases Respiratory Distress Syndrome Radiography, Thoracic
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