AIMC Topic: Thorax

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[A preliminary investigation on a deep learning convolutional neural networks based pulmonary tuberculosis CT diagnostic model].

Zhonghua jie he he hu xi za zhi = Zhonghua jiehe he huxi zazhi = Chinese journal of tuberculosis and respiratory diseases May 12, 2021
To evaluate the clinical value of a pulmonary tuberculosis CT diagnostic model based on deep learning convolutional neural networks (CNN). From March 2017 to March 2018,a total of 1 764 patients with positive sputum for tuberculous bacterium and ha...
Humans Neural Networks, Computer Deep Learning Tuberculosis, Pulmonary Tomography, X-Ray Computed Thorax Female Male
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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...
Tomography, X-Ray Computed Lung Deep Learning Image Processing, Computer-Assisted Thorax
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Determination of disease severity in COVID-19 patients using deep learning in chest X-ray images.

Diagnostic and interventional radiology (Ankara, Turkey) Jan 1, 2021
PURPOSE: Chest X-ray plays a key role in diagnosis and management of COVID-19 patients and imaging features associated with clinical elements may assist with the development or validation of automated image analysis tools. We aimed to identify associ...
COVID-19 Retrospective Studies Female Humans Thorax Feasibility Studies Radiography, Thoracic Comorbidity Severity of Illness Index Deep Learning Age Factors Italy Radiologists Adult SARS-CoV-2 Male Aged Middle Aged
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[Artificial intelligence-based algorithms : Decision-making support for computed tomography of the chest].

Der Radiologe Oct 1, 2020
Artificial intelligence (AI) algorithms are increasingly used in radiology. The main areas of application are, for example, the detection of lung lesions and the diagnosis of chronic obstructive and interstitial lung diseases. The aim of our study wa...
Lung Diseases, Interstitial Thorax Humans Artificial Intelligence Algorithms Tomography, X-Ray Computed Decision Support Systems, Clinical
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A Weakly-Supervised Framework for COVID-19 Classification and Lesion Localization From Chest CT.

IEEE transactions on medical imaging Aug 1, 2020
Accurate and rapid diagnosis of COVID-19 suspected cases plays a crucial role in timely quarantine and medical treatment. Developing a deep learning-based model for automatic COVID-19 diagnosis on chest CT is helpful to counter the outbreak of SARS-C...
Thorax Betacoronavirus Pneumonia, Viral Humans Coronavirus Infections Pandemics Image Interpretation, Computer-Assisted Male COVID-19 Middle Aged Lung Retrospective Studies Adolescent Tomography, X-Ray Computed Child Female Supervised Machine Learning SARS-CoV-2 Aged, 80 and over Aged Young Adult Adult
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Lung CT Image Registration through Landmark-constrained Learning with Convolutional Neural Network.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2020
Accurate registration of lung computed tomography (CT) image is a significant task in thorax image analysis. Recently deep learning-based medical image registration methods develop fast and achieve promising performance on accuracy and speed. However...
Neural Networks, Computer Tomography, X-Ray Computed Lung Thorax
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An Attention-Guided Deep Neural Network for Annotating Abnormalities in Chest X-ray Images: Visualization of Network Decision Basis.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2020
Despite the potential of deep convolutional neural networks for classification of thorax diseases from chest X-ray images, this task is still challenging as it is categorized as a weakly supervised learning problem, and deep neural networks in genera...
Algorithms Thorax Neural Networks, Computer X-Rays Attention
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Lung Region Segmentation in Chest X-Ray Images using Deep Convolutional Neural Networks.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2020
Lung cancer is, by far, the leading cause of cancer death in the world. Tools for automated medical imaging analysis development of a Computer-Aided Diagnosis method comprises several tasks. In general, the first one is the segmentation of region of ...
Thorax Neural Networks, Computer X-Rays Lung Diagnosis, Computer-Assisted
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Dense-Unet: a light model for lung fields segmentation in Chest X-Ray images.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2020
Automatic and accurate lung segmentation in chest X-ray (CXR) images is fundamental for computer-aided diagnosis systems since the lung is the region of interest in many diseases and also it can reveal useful information by its contours. While deep l...
Neural Networks, Computer X-Rays Lung Diagnosis, Computer-Assisted Thorax
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Multi-View Ensemble Convolutional Neural Network to Improve Classification of Pneumonia in Low Contrast Chest X-Ray Images.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2020
Pneumonia is one of the leading causes of childhood mortality worldwide. Chest x-ray (CXR) can aid the diagnosis of pneumonia, but in the case of low contrast images, it is important to include computational tools to aid specialists. Deep learning is...
Pneumonia Thorax X-Rays Deep Learning Child Humans Neural Networks, Computer
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