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

Showing 71 to 80 of 116 articles

Classification by a stacking model using CNN features for COVID-19 infection diagnosis.

Journal of X-ray science and technology Jan 1, 2022
Affecting millions of people all over the world, the COVID-19 pandemic has caused the death of hundreds of thousands of people since its beginning. Examinations also found that even if the COVID-19 patients initially survived the coronavirus, pneumon...
COVID-19 Algorithms Humans Pandemics COVID-19 Testing Pneumonia, Viral SARS-CoV-2 Deep Learning
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Impact of novel deep learning image reconstruction algorithm on diagnosis of contrast-enhanced liver computed tomography imaging: Comparing to adaptive statistical iterative reconstruction algorithm.

Journal of X-ray science and technology Jan 1, 2021
OBJECTIVE: To assess clinical application of applying deep learning image reconstruction (DLIR) algorithm to contrast-enhanced portal venous phase liver computed tomography (CT) for improving image quality and lesions detection rate compared with usi...
Radiation Dosage Deep Learning Image Processing, Computer-Assisted Algorithms Liver Tomography, X-Ray Computed Radiographic Image Interpretation, Computer-Assisted Humans
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Analysis of segmentation of lung parenchyma based on deep learning methods.

Journal of X-ray science and technology Jan 1, 2021
Precise segmentation of lung parenchyma is essential for effective analysis of the lung. Due to the obvious contrast and large regional area compared to other tissues in the chest, lung tissue is less difficult to segment. Special attention to detail...
Lung Deep Learning Image Processing, Computer-Assisted Thorax Tomography, X-Ray Computed
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Tuberculosis detection in chest X-ray using Mayfly-algorithm optimized dual-deep-learning features.

Journal of X-ray science and technology Jan 1, 2021
World-Health-Organization (WHO) has listed Tuberculosis (TB) as one among the top 10 reasons for death and an early diagnosis will help to cure the patient by giving suitable treatment. TB usually affects the lungs and an accurate bio-imaging scheme ...
Ephemeroptera Tuberculosis X-Rays Humans Animals Algorithms Deep Learning
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Deep learning assistance for tuberculosis diagnosis with chest radiography in low-resource settings.

Journal of X-ray science and technology Jan 1, 2021
Tuberculosis (TB) is a major health issue with high mortality rates worldwide. Recently, tremendous researches of artificial intelligence (AI) have been conducted targeting at TB to reduce the diagnostic burden. However, most researches are conducted...
Humans Artificial Intelligence Deep Learning Tuberculosis Radiography Radiologists
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A preliminary evaluation study of applying a deep learning image reconstruction algorithm in low-kilovolt scanning of upper abdomen.

Journal of X-ray science and technology Jan 1, 2021
OBJECTIVE: To investigate feasibility of applying deep learning image reconstruction (DLIR) algorithm in a low-kilovolt enhanced scan of the upper abdomen.
Radiation Dosage Radiographic Image Interpretation, Computer-Assisted Algorithms Image Processing, Computer-Assisted Deep Learning Abdomen Humans
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Deep learning supported disease detection with multi-modality image fusion.

Journal of X-ray science and technology Jan 1, 2021
Multi-modal image fusion techniques aid the medical experts in better disease diagnosis by providing adequate complementary information from multi-modal medical images. These techniques enhance the effectiveness of medical disorder analysis and class...
Algorithms Deep Learning Image Processing, Computer-Assisted Entropy Neural Networks, Computer
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A few-shot segmentation method for prohibited item inspection.

Journal of X-ray science and technology Jan 1, 2021
BACKGROUND: With the rapid development of deep learning, several neural network models have been proposed for automatic segmentation of prohibited items. These methods usually based on a substantial amount of labelled training data. However, for some...
Neural Networks, Computer Image Processing, Computer-Assisted
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A feasibility study of realizing low-dose abdominal CT using deep learning image reconstruction algorithm.

Journal of X-ray science and technology Jan 1, 2021
OBJECTIVES: To explore the feasibility of achieving diagnostic images in low-dose abdominal CT using a Deep Learning Image Reconstruction (DLIR) algorithm.
Humans Algorithms Image Processing, Computer-Assisted Radiographic Image Interpretation, Computer-Assisted Tomography, X-Ray Computed Deep Learning Feasibility Studies Radiation Dosage
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Dual residual convolutional neural network (DRCNN) for low-dose CT imaging.

Journal of X-ray science and technology Jan 1, 2021
The excessive radiation doses in the application of computed tomography (CT) technology pose a threat to the health of patients. However, applying a low radiation dose in CT can result in severe artifacts and noise in the captured images, thus affect...
Tomography, X-Ray Computed Artifacts Humans Image Processing, Computer-Assisted Signal-To-Noise Ratio Neural Networks, Computer
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