AIMC Topic: Radiographic Image Interpretation, Computer-Assisted

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Exploiting Multiple Optimizers with Transfer Learning Techniques for the Identification of COVID-19 Patients.

Journal of healthcare engineering Nov 23, 2020
Due to the rapid spread of COVID-19 and its induced death worldwide, it is imperative to develop a reliable tool for the early detection of this disease. Chest X-ray is currently accepted to be one of the reliable means for such a detection purpose. ...
Sensitivity and Specificity COVID-19 Radiography, Thoracic Databases, Factual Lung Reproducibility of Results Radiographic Image Interpretation, Computer-Assisted SARS-CoV-2 Humans Early Diagnosis Machine Learning Software
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The image quality of deep-learning image reconstruction of chest CT images on a mediastinal window setting.

Clinical radiology Nov 19, 2020
AIM: To assess the image quality of deep-learning image reconstruction (DLIR) of chest computed tomography (CT) images on a mediastinal window setting in comparison to an adaptive statistical iterative reconstruction (ASiR-V).
Radiographic Image Interpretation, Computer-Assisted Radiography, Thoracic Mediastinum Thoracic Diseases Aged Male Middle Aged Deep Learning Humans Retrospective Studies Tomography, X-Ray Computed Female
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Improving Image Quality and Reducing Radiation Dose for Pediatric CT by Using Deep Learning Reconstruction.

Radiology Nov 17, 2020
Background CT deep learning reconstruction (DLR) algorithms have been developed to remove image noise. How the DLR affects image quality and radiation dose reduction has yet to be fully investigated. Purpose To investigate a DLR algorithm's dose redu...
Radiographic Image Interpretation, Computer-Assisted Quality Improvement Pediatrics Radiation Dosage Hepatic Veins Mesenteric Artery, Superior Common Bile Duct Azygos Vein Deep Learning Adolescent Child, Preschool Child Young Adult Adult Male Humans Retrospective Studies Tomography, X-Ray Computed Female
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An efficient mixture of deep and machine learning models for COVID-19 diagnosis in chest X-ray images.

PloS one Nov 17, 2020
A newly emerged coronavirus (COVID-19) seriously threatens human life and health worldwide. In coping and fighting against COVID-19, the most critical step is to effectively screen and diagnose infected patients. Among them, chest X-ray imaging techn...
Coronavirus Infections Thorax Betacoronavirus Pneumonia, Viral Tomography, X-Ray Computed Humans SARS-CoV-2 Pandemics Deep Learning COVID-19 Radiographic Image Interpretation, Computer-Assisted
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Multiclass machine learning vs. conventional calculators for stroke/CVD risk assessment using carotid plaque predictors with coronary angiography scores as gold standard: a 500 participants study.

The international journal of cardiovascular imaging Nov 12, 2020
Machine learning (ML)-based algorithms for cardiovascular disease (CVD) risk assessment have shown promise in clinical decisions. However, they usually predict binary events using only conventional risk factors. Our overall goal was to develop the "m...
Humans Machine Learning Decision Support Techniques Prognosis Heart Disease Risk Factors Plaque, Atherosclerotic Carotid Stenosis Coronary Stenosis Diagnosis, Computer-Assisted Cross-Sectional Studies Female Pilot Projects Male Ultrasonography Predictive Value of Tests Reproducibility of Results Middle Aged Support Vector Machine Coronary Angiography Aged Risk Assessment Radiographic Image Interpretation, Computer-Assisted Stroke
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Neural Network Vessel Lumen Regression for Automated Lumen Cross-Section Segmentation in Cardiovascular Image-Based Modeling.

Cardiovascular engineering and technology Nov 11, 2020
PURPOSE: We accelerate a pathline-based cardiovascular model building method by training machine learning models to directly predict vessel lumen surface points from computed tomography (CT) and magnetic resonance (MR) medical image data.
Humans Neural Networks, Computer Reproducibility of Results Diagnosis, Computer-Assisted Computed Tomography Angiography Predictive Value of Tests Models, Cardiovascular Radiographic Image Interpretation, Computer-Assisted Patient-Specific Modeling Automation Blood Vessels Magnetic Resonance Angiography
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Deep learning analysis provides accurate COVID-19 diagnosis on chest computed tomography.

European journal of radiology Nov 4, 2020
INTRODUCTION: Computed Tomography is an essential diagnostic tool in the management of COVID-19. Considering the large amount of examinations in high case-load scenarios, an automated tool could facilitate and save critical time in the diagnosis and ...
Reproducibility of Results Sensitivity and Specificity Male Middle Aged Humans COVID-19 Tomography, X-Ray Computed Female Lung Deep Learning ROC Curve Radiographic Image Interpretation, Computer-Assisted
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The detection of lung cancer using massive artificial neural network based on soft tissue technique.

BMC medical informatics and decision making Oct 31, 2020
BACKGROUND: A proposed computer aided detection (CAD) scheme faces major issues during subtle nodule recognition. However, radiologists have not noticed subtle nodules in beginning stage of lung cancer while a proposed CAD scheme recognizes non subtl...
Neural Networks, Computer Tomography, X-Ray Computed Sensitivity and Specificity Lung Lung Neoplasms Solitary Pulmonary Nodule Radiographic Image Interpretation, Computer-Assisted Image Interpretation, Computer-Assisted Humans
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The importance of standardisation - COVID-19 CT & Radiograph Image Data Stock for deep learning purpose.

Computers in biology and medicine Oct 28, 2020
With the number of affected individuals still growing world-wide, the research on COVID-19 is continuously expanding. The deep learning community concentrates their efforts on exploring if neural networks can potentially support the diagnosis using C...
Lung Humans Deep Learning COVID-19 Tomography, X-Ray Computed Radiographic Image Interpretation, Computer-Assisted SARS-CoV-2
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Deep learning reconstruction of equilibrium phase CT images in obese patients.

European journal of radiology Oct 28, 2020
PURPOSE: To compare abdominal equilibrium phase (EP) CT images of obese and non-obese patients to identify the reconstruction method that preserves the diagnostic value of images obtained in obese patients.
Obesity Radiographic Image Interpretation, Computer-Assisted Radiation Dosage Algorithms Tomography, X-Ray Computed Deep Learning Humans
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