AI Medical Compendium Journal:
Journal of X-ray science and technology

Showing 101 to 110 of 116 articles

Breast mass detection and diagnosis using fused features with density.

Journal of X-ray science and technology Jan 1, 2019
BACKGROUND: The morbidity of breast cancer has been increased in these years and ranked the first of all female diseases. Computer-aided diagnosis techniques for mammograms can help radiologists find early breast lesions. In mammograms, the degree of...
Female Aged Adult Humans Databases, Factual ROC Curve Unsupervised Machine Learning Mammography Breast Neoplasms Middle Aged Radiographic Image Interpretation, Computer-Assisted Breast
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Automatic hip geometric feature extraction in DXA imaging using regional random forest.

Journal of X-ray science and technology Jan 1, 2019
BACKGROUND: Hip fracture is considered one of the salient disability factors across the global population. People with hip fractures are prone to become permanently disabled or die from complications. Although currently the premier determiner, bone m...
Pelvic Bones Decision Trees Hip Fractures Humans Machine Learning Image Interpretation, Computer-Assisted Absorptiometry, Photon Algorithms
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Expert knowledge-infused deep learning for automatic lung nodule detection.

Journal of X-ray science and technology Jan 1, 2019
BACKGROUND: Computer aided detection (CADe) of pulmonary nodules from computed tomography (CT) is crucial for early diagnosis of lung cancer. Self-learned features obtained by training datasets via deep learning have facilitated CADe of the nodules. ...
Tomography, X-Ray Computed Sensitivity and Specificity Deep Learning Humans Neural Networks, Computer Solitary Pulmonary Nodule Radiographic Image Interpretation, Computer-Assisted Knowledge Bases Lung Neoplasms Multiple Pulmonary Nodules
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Comparison of medical image classification accuracy among three machine learning methods.

Journal of X-ray science and technology Jan 1, 2018
BACKGROUND: Low-quality medical images may influence the accuracy of the machine learning process.
Support Vector Machine Diagnostic Imaging Deep Learning Humans Image Processing, Computer-Assisted Machine Learning Neural Networks, Computer Databases, Factual
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Femur segmentation in DXA imaging using a machine learning decision tree.

Journal of X-ray science and technology Jan 1, 2018
BACKGROUND: Accurate measurement of bone mineral density (BMD) in dual-energy X-ray absorptiometry (DXA) is essential for proper diagnosis of osteoporosis. Calculation of BMD requires precise bone segmentation and subtraction of soft tissue absorptio...
Femur Humans Decision Trees Image Interpretation, Computer-Assisted Machine Learning Absorptiometry, Photon Osteoporosis
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Digital radiography image denoising using a generative adversarial network.

Journal of X-ray science and technology Jan 1, 2018
Statistical noise may degrade the x-ray image quality of digital radiography (DR) system. This corruption can be alleviated by extending exposure time of detectors and increasing the intensity of radiation. However, in some instances, such as the sec...
Image Processing, Computer-Assisted Unsupervised Machine Learning Radiographic Image Enhancement Neural Networks, Computer
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Low dose CT reconstruction via L1 norm dictionary learning using alternating minimization algorithm and balancing principle.

Journal of X-ray science and technology Jan 1, 2018
Excessive radiation exposure in computed tomography (CT) scans increases the chance of developing cancer and has become a major clinical concern. Recently, statistical iterative reconstruction (SIR) with l0-norm dictionary learning regularization has...
Humans Algorithms Animals Lung Tomography, X-Ray Computed Sheep Phantoms, Imaging Image Processing, Computer-Assisted Supervised Machine Learning
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Projection decomposition algorithm for dual-energy computed tomography via deep neural network.

Journal of X-ray science and technology Jan 1, 2018
BACKGROUND: Dual-energy computed tomography (DECT) has been widely used to improve identification of substances from different spectral information. Decomposition of the mixed test samples into two materials relies on a well-calibrated material decom...
Phantoms, Imaging Neural Networks, Computer Algorithms Image Processing, Computer-Assisted Humans Tomography, X-Ray Computed Signal-To-Noise Ratio
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A hybrid CNN feature model for pulmonary nodule malignancy risk differentiation.

Journal of X-ray science and technology Jan 1, 2018
The malignancy risk differentiation of pulmonary nodule is one of the most challenge tasks of computer-aided diagnosis (CADx). Most recently reported CADx methods or schemes based on texture and shape estimation have shown relatively satisfactory on ...
Lung Diagnosis, Computer-Assisted Early Detection of Cancer Risk Lung Neoplasms Neural Networks, Computer Machine Learning Algorithms Humans
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Enhancement of digital radiography image quality using a convolutional neural network.

Journal of X-ray science and technology Jan 1, 2017
Digital radiography system is widely used for noninvasive security check and medical imaging examination. However, the system has a limitation of lower image quality in spatial resolution and signal to noise ratio. In this study, we explored whether ...
Radiographic Image Enhancement Reproducibility of Results Humans Image Processing, Computer-Assisted Neural Networks, Computer Radiographic Image Interpretation, Computer-Assisted
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