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

Showing 61 to 70 of 116 articles

Parameter tuning in machine learning based on radiomics biomarkers of lung cancer.

Journal of X-ray science and technology Jan 1, 2022
BACKGROUND: Lung cancer is one of the most common cancers, and early diagnosis and intervention can improve cancer cure rate.
Lung ROC Curve Biomarkers Support Vector Machine Retrospective Studies Lung Neoplasms Humans Machine Learning
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Leukemia classification using the deep learning method of CNN.

Journal of X-ray science and technology Jan 1, 2022
BACKGROUND: Processing Low-Intensity Medical Images (LI-MI) is difficult as outcomes are varied when it comes to manual examination, which is also a time-consuming process.
Deep Learning Bayes Theorem Neural Networks, Computer Machine Learning Leukemia Humans
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Optimized chest X-ray image semantic segmentation networks for COVID-19 early detection.

Journal of X-ray science and technology Jan 1, 2022
BACKGROUND: Although detection of COVID-19 from chest X-ray radiography (CXR) images is faster than PCR sputum testing, the accuracy of detecting COVID-19 from CXR images is lacking in the existing deep learning models.
Radiography X-Rays COVID-19 Humans Semantics SARS-CoV-2 Deep Learning
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Impact of deep learning-based image reconstruction on image quality compared with adaptive statistical iterative reconstruction-Veo in renal and adrenal computed tomography.

Journal of X-ray science and technology Jan 1, 2022
OBJECTIVE: To evaluate image quality of deep learning-based image reconstruction (DLIR) in contrast-enhanced renal and adrenal computed tomography (CT) compared with adaptive statistical iterative reconstruction-Veo (ASiR-V).
Algorithms Tomography, X-Ray Computed Humans Deep Learning Image Processing, Computer-Assisted Radiation Dosage Radiographic Image Interpretation, Computer-Assisted
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AI-driven deep convolutional neural networks for chest X-ray pathology identification.

Journal of X-ray science and technology Jan 1, 2022
BACKGROUND: Chest X-ray images are widely used to detect many different lung diseases. However, reading chest X-ray images to accurately detect and classify different lung diseases by doctors is often difficult with large inter-reader variability. Th...
Algorithms SARS-CoV-2 X-Rays Neural Networks, Computer Deep Learning COVID-19 Humans
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A coronary artery CTA segmentation approach based on deep learning.

Journal of X-ray science and technology Jan 1, 2022
Presence of plaque and coronary artery stenosis are the main causes of coronary heart disease. Detection of plaque and coronary artery segmentation have become the first choice in detecting coronary artery disease. The purpose of this study is to inv...
Coronary Vessels Computed Tomography Angiography Deep Learning Image Processing, Computer-Assisted Algorithms Tomography, X-Ray Computed Humans
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UBNet: Deep learning-based approach for automatic X-ray image detection of pneumonia and COVID-19 patients.

Journal of X-ray science and technology Jan 1, 2022
BACKGROUND: Analysis of chest X-ray images is one of the primary standards in diagnosing patients with COVID-19 and pneumonia, which is faster than using PCR Swab method. However, accuracy of using X-ray images needs to be improved.
Deep Learning X-Rays Algorithms SARS-CoV-2 Pneumonia, Viral Neural Networks, Computer Humans COVID-19
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Computer-aided COVID-19 diagnosis and a comparison of deep learners using augmented CXRs.

Journal of X-ray science and technology Jan 1, 2022
BACKGROUND: Coronavirus Disease 2019 (COVID-19) is contagious, producing respiratory tract infection, caused by a newly discovered coronavirus. Its death toll is too high, and early diagnosis is the main problem nowadays. Infected people show a varie...
COVID-19 Computers SARS-CoV-2 Humans Deep Learning COVID-19 Testing
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Application of deep learning image reconstruction algorithm to improve image quality in CT angiography of children with Takayasu arteritis.

Journal of X-ray science and technology Jan 1, 2022
BACKGROUND: The inflammatory indexes of children with Takayasu arteritis (TAK) usually tend to be normal immediately after treatment, therefore, CT angiography (CTA) has become an important method to evaluate the status of TAK and sometime is even mo...
Computed Tomography Angiography Deep Learning Takayasu Arteritis Radiographic Image Interpretation, Computer-Assisted Humans Child Adolescent Radiation Dosage Child, Preschool Algorithms Image Processing, Computer-Assisted
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Novel U-net based deep neural networks for transmission tomography.

Journal of X-ray science and technology Jan 1, 2022
BACKGROUND: The fusion of computer tomography and deep learning is an effective way of achieving improved image quality and artifact reduction in reconstructed images.
Image Processing, Computer-Assisted Artifacts Signal-To-Noise Ratio Neural Networks, Computer Tomography, X-Ray Computed
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