AIMC Topic: Radiographic Image Interpretation, Computer-Assisted

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Variable generalization performance of a deep learning model to detect pneumonia in chest radiographs: A cross-sectional study.

PLoS medicine Nov 6, 2018
BACKGROUND: There is interest in using convolutional neural networks (CNNs) to analyze medical imaging to provide computer-aided diagnosis (CAD). Recent work has suggested that image classification CNNs may not generalize to new data as well as previ...
Cross-Sectional Studies Male Middle Aged Diagnosis, Computer-Assisted Retrospective Studies Reproducibility of Results Female Aged Adult Humans Predictive Value of Tests Radiographic Image Interpretation, Computer-Assisted Radiology Information Systems Radiography, Thoracic Deep Learning United States Pneumonia
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Machine learning to predict lung nodule biopsy method using CT image features: A pilot study.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Nov 3, 2018
Computed tomography (CT)-based screening on lung cancer mortality is poised to make lung nodule management a growing public health problem. Biopsy and pathologic analysis of suspicious nodules is necessary to ensure accurate diagnosis and appropriate...
Solitary Pulmonary Nodule Predictive Value of Tests Biopsy Radiographic Image Interpretation, Computer-Assisted Pilot Projects Imaging, Three-Dimensional Humans Lung Neoplasms Machine Learning Tomography, X-Ray Computed
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The evolution of image reconstruction for CT-from filtered back projection to artificial intelligence.

European radiology Oct 30, 2018
The first CT scanners in the early 1970s already used iterative reconstruction algorithms; however, lack of computational power prevented their clinical use. In fact, it took until 2009 for the first iterative reconstruction algorithms to come commer...
Radiation Dosage Humans Tomography, X-Ray Computed Radiographic Image Interpretation, Computer-Assisted Artificial Intelligence Algorithms
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Rise of the machines.

Tidsskrift for den Norske laegeforening : tidsskrift for praktisk medicin, ny raekke Oct 30, 2018
Robotics Radiographic Image Interpretation, Computer-Assisted Humans Artificial Intelligence
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Artificial intelligence machine learning-based coronary CT fractional flow reserve (CT-FFR): Impact of iterative and filtered back projection reconstruction techniques.

Journal of cardiovascular computed tomography Oct 26, 2018
BACKGROUND: The influence of computed tomography (CT) reconstruction algorithms on the performance of machine-learning-based CT-derived fractional flow reserve (CT-FFR) has not been investigated. CT-FFR values and processing time of two reconstructio...
Coronary Stenosis Humans Fractional Flow Reserve, Myocardial Machine Learning Retrospective Studies Male Workflow Middle Aged Coronary Angiography Female Severity of Illness Index Coronary Vessels Radiographic Image Interpretation, Computer-Assisted Reproducibility of Results Predictive Value of Tests Computed Tomography Angiography Coronary Artery Disease Aged
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Iterative quality enhancement via residual-artifact learning networks for low-dose CT.

Physics in medicine and biology Oct 23, 2018
Radiation exposure and the associated risk of cancer for patients in computed tomography (CT) scans have been major clinical concerns. The radiation exposure can be reduced effectively via lowering the x-ray tube current (mA). However, this strategy ...
Machine Learning Algorithms Tomography, X-Ray Computed Humans Neural Networks, Computer Radiation Dosage Plaque, Atherosclerotic Radionuclide Imaging Radiation Exposure Radiographic Image Interpretation, Computer-Assisted Artifacts Brain Diseases
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Coronary artery centerline extraction in cardiac CT angiography using a CNN-based orientation classifier.

Medical image analysis Oct 22, 2018
Coronary artery centerline extraction in cardiac CT angiography (CCTA) images is a prerequisite for evaluation of stenoses and atherosclerotic plaque. In this work, we propose an algorithm that extracts coronary artery centerlines in CCTA using a con...
Humans Retrospective Studies Contrast Media Neural Networks, Computer Algorithms Computed Tomography Angiography Radiographic Image Interpretation, Computer-Assisted Netherlands Coronary Vessels
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Machine-learning integration of CT histogram analysis to evaluate the composition of atherosclerotic plaques: Validation with IB-IVUS.

Journal of cardiovascular computed tomography Oct 21, 2018
BACKGROUND: To determine whether machine learning with histogram analysis of coronary CT angiography (CCTA) yields higher diagnostic performance for coronary plaque characterization than the conventional cut-off method using the median CT number.
Multidetector Computed Tomography Male Female Humans Predictive Value of Tests Reproducibility of Results Coronary Artery Disease Plaque, Atherosclerotic Coronary Angiography Aged Machine Learning Computed Tomography Angiography Coronary Vessels Retrospective Studies Ultrasonography, Interventional Radiographic Image Interpretation, Computer-Assisted
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Improvement of fully automated airway segmentation on volumetric computed tomographic images using a 2.5 dimensional convolutional neural net.

Medical image analysis Oct 19, 2018
We propose a novel airway segmentation method in volumetric chest computed tomography (CT) and evaluate its performance on multiple datasets. The segmentation is performed voxel-by-voxel by a 2.5D convolutional neural net (2.5D CNN) trained in a supe...
Tomography, X-Ray Computed Reproducibility of Results Pulmonary Disease, Chronic Obstructive Radiographic Image Interpretation, Computer-Assisted Respiratory Function Tests Neural Networks, Computer Humans Algorithms
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[Will radiologists be replaced by artificial intelligence?].

Tidsskrift for den Norske laegeforening : tidsskrift for praktisk medicin, ny raekke Oct 19, 2018
Radiographic Image Interpretation, Computer-Assisted Humans Artificial Intelligence Neural Networks, Computer Machine Learning Radiologists
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