AIMC Topic: Tomography, X-Ray Computed

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[Supplementing a Web-based Exposure Estimation System with Deep Learning for Automatic Classification of CT Images to Increase the Efficiency of Effective Dose Estimation].

Nihon Hoshasen Gijutsu Gakkai zasshi Jan 1, 2020
PURPOSE: Web-based exposure estimation systems are advantageous for estimating exposure doses for computed tomography (CT) scans. However, such systems depend on the imaging conditions of the slices, and a considerable amount of time and effort is ne...
Internet Neural Networks, Computer Radionuclide Imaging Tomography, X-Ray Computed Deep Learning
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Multi-level 3D Densenets for False-positive Reduction in Lung Nodule Detection Based on Chest Computed Tomography.

Current medical imaging Jan 1, 2020
OBJECTIVE: False-positive nodule reduction is a crucial part of a computer-aided detection (CADe) system, which assists radiologists in accurate lung nodule detection. In this research, a novel scheme using multi-level 3D DenseNet framework is propos...
Humans Neural Networks, Computer Imaging, Three-Dimensional Lung Neoplasms Tomography, X-Ray Computed Lung
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AI-Driven COVID-19 Tools to Interpret, Quantify Lung Images.

IEEE pulse Jan 1, 2020
Qualitative interpretation is a good thing when it comes to reading lung images in the fight against coronavirus 2019 disease (COVID-19), but quantitative analysis makes radiology reporting much more comprehensive. To that end, several research group...
Artificial Intelligence Pandemics COVID-19 Algorithms Humans Radiographic Image Interpretation, Computer-Assisted Tomography, X-Ray Computed Betacoronavirus Coronavirus Infections SARS-CoV-2 Pneumonia, Viral Lung
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Detection of coronavirus disease from X-ray images using deep learning and transfer learning algorithms.

Journal of X-ray science and technology Jan 1, 2020
OBJECTIVE: This study aims to employ the advantages of computer vision and medical image analysis to develop an automated model that has the clinical potential for early detection of novel coronavirus (COVID-19) infected disease.
Tomography, X-Ray Computed Reproducibility of Results SARS-CoV-2 Humans Pandemics Neural Networks, Computer COVID-19 Lung Coronavirus Infections Betacoronavirus Deep Learning Algorithms Early Diagnosis Pneumonia, Viral Pneumonia
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Identification of COVID-19 samples from chest X-Ray images using deep learning: A comparison of transfer learning approaches.

Journal of X-ray science and technology Jan 1, 2020
BACKGROUND: The novel coronavirus disease 2019 (COVID-19) constitutes a public health emergency globally. The number of infected people and deaths are proliferating every day, which is putting tremendous pressure on our social and healthcare system. ...
Tomography, X-Ray Computed Reproducibility of Results SARS-CoV-2 Pneumonia Coronavirus Infections Deep Learning Diagnosis, Differential COVID-19 Radiography, Thoracic Betacoronavirus Algorithms Humans Pneumonia, Viral Databases, Factual Neural Networks, Computer Pandemics
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Developing and verifying automatic detection of active pulmonary tuberculosis from multi-slice spiral CT images based on deep learning.

Journal of X-ray science and technology Jan 1, 2020
OBJECTIVE: Diagnosis of tuberculosis (TB) in multi-slice spiral computed tomography (CT) images is a difficult task in many TB prevalent locations in which experienced radiologists are lacking. To address this difficulty, we develop an automated dete...
Child Radiographic Image Interpretation, Computer-Assisted Tuberculosis, Pulmonary Deep Learning Adolescent Child, Preschool Aged Aged, 80 and over Young Adult Humans Middle Aged Lung Tomography, X-Ray Computed Algorithms Female Adult Male
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Deep learning-based CAD schemes for the detection and classification of lung nodules from CT images: A survey.

Journal of X-ray science and technology Jan 1, 2020
BACKGROUND: Lung cancer is the most common cancer in the world. Computed tomography (CT) is the standard medical imaging modality for early lung nodule detection and diagnosis that improves patient's survival rate. Recently, deep learning algorithms,...
Surveys and Questionnaires Lung Neoplasms Radiographic Image Interpretation, Computer-Assisted Humans Neural Networks, Computer Databases, Factual Lung Deep Learning Tomography, X-Ray Computed Sensitivity and Specificity
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Cat Swarm Optimization based Functional Link Multilayer Perceptron for Suppression of Gaussian and Impulse Noise from Computed Tomography Images.

Current medical imaging Jan 1, 2020
BACKGROUND: The Gaussian and impulse noises corrupt the Computed Tomography (CT) images either individually or collectively, and the conventional fixed filters do not have the potential to suppress these noise.
Humans Neural Networks, Computer Algorithms Signal-To-Noise Ratio Tomography, X-Ray Computed Signal Processing, Computer-Assisted Radiographic Image Interpretation, Computer-Assisted
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CT-Based Quantitative Analysis for Pathological Features Associated With Postoperative Recurrence and Potential Application Upon Artificial Intelligence: A Narrative Review With a Focus on Chronic Subdural Hematomas.

Molecular imaging Jan 1, 2020
Chronic subdural hematomas (CSDHs) frequently affect the elderly population. The postoperative recurrence rate of CSDHs is high, ranging from 3% to 20%. Both qualitative and quantitative analyses have been explored to investigate the mechanisms under...
Humans Artificial Intelligence Tomography, X-Ray Computed Postoperative Care Recurrence Hematoma, Subdural, Chronic
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3D Cascaded Convolutional Networks for Multi-vertebrae Segmentation.

Current medical imaging Jan 1, 2020
BACKGROUND: Automatic approach to vertebrae segmentation from computed tomography (CT) images is very important in clinical applications. As the intricate appearance and variable architecture of vertebrae across the population, cognate constructions ...
Spine Spinal Injuries Female Young Adult Adult Humans Male Neural Networks, Computer Adolescent Tomography, X-Ray Computed Imaging, Three-Dimensional Radiographic Image Interpretation, Computer-Assisted
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