AIMC Topic: Thorax

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Automatic Detection and Classification of Rib Fractures on Thoracic CT Using Convolutional Neural Network: Accuracy and Feasibility.

Korean journal of radiology Jul 1, 2020
OBJECTIVE: To evaluate the performance of a convolutional neural network (CNN) model that can automatically detect and classify rib fractures, and output structured reports from computed tomography (CT) images.
Young Adult Adult Male Female Aged Humans Aged, 80 and over Neural Networks, Computer Rib Fractures Tomography, X-Ray Computed Area Under Curve Feasibility Studies Thorax Middle Aged ROC Curve Image Processing, Computer-Assisted
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Clinical Implementation of Deep Learning in Thoracic Radiology: Potential Applications and Challenges.

Korean journal of radiology May 1, 2020
Chest X-ray radiography and computed tomography, the two mainstay modalities in thoracic radiology, are under active investigation with deep learning technology, which has shown promising performance in various tasks, including detection, classificat...
Radiography, Thoracic Thorax Tomography, X-Ray Computed Deep Learning Image Processing, Computer-Assisted Humans
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Development and Validation of a Deep Learning-based Automatic Detection Algorithm for Active Pulmonary Tuberculosis on Chest Radiographs.

Clinical infectious diseases : an official publication of the Infectious Diseases Society of America Aug 16, 2019
BACKGROUND: Detection of active pulmonary tuberculosis on chest radiographs (CRs) is critical for the diagnosis and screening of tuberculosis. An automated system may help streamline the tuberculosis screening process and improve diagnostic performan...
Thorax Adult Sensitivity and Specificity Male Female Aged Middle Aged Deep Learning ROC Curve Radiography Tuberculosis, Pulmonary Automation Humans Algorithms
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Hybrid Neural Networks for Mortality Prediction from LDCT 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, 2019
Known for its high morbidity and mortality rates, lung cancer poses a significant threat to human health and well-being. However, the same population is also at high risk for other deadly diseases, such as cardiovascular disease. Since Low-Dose CT (L...
Lung Neoplasms Risk Assessment Coronary Artery Disease Deep Learning Thorax Humans Neural Networks, Computer Tomography, X-Ray Computed
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Number and Angle Analysis in UWB Radar Deployment for Vital Sign Monitoring.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2019
In recent years, more studies focus on the UltraWide Band (UWB) radar to provide a noncontact vital sign monitoring service. To further improve the accuracy of vital sign monitoring, the UWB radar network composed by multiple radars is considered for...
Neural Networks, Computer Data Collection Thorax Radar
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Machine Learning and Deep Neural Networks in Thoracic and Cardiovascular Imaging.

Journal of thoracic imaging May 1, 2019
Advances in technology have always had the potential and opportunity to shape the practice of medicine, and in no medical specialty has technology been more rapidly embraced and adopted than radiology. Machine learning and deep neural networks promis...
Humans Thorax Cardiovascular System Thoracic Diseases Cardiovascular Diseases Image Processing, Computer-Assisted Neural Networks, Computer Diagnostic Imaging Machine Learning
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[The future of computer-aided diagnostics in chest computed tomography].

Khirurgiia Jan 1, 2019
Recently, more and more attention has been paid to the utility of artificial intelligence in medicine. Radiology differs from other medical specialties with its high digitalization, so most software developers operationalize this area of medicine. Th...
Reproducibility of Results Diagnosis, Computer-Assisted Lung Neoplasms Early Detection of Cancer Thorax Machine Learning Forecasting Tomography, X-Ray Computed Humans
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Reply to Mummadi et al.: Overfitting and Use of Mismatched Cohorts in Deep Learning Models: Preventable Design Limitations.

American journal of respiratory and critical care medicine Aug 15, 2018
Thorax Tomography, X-Ray Computed Deep Learning Humans Smokers Prognosis
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Fully Automated Spleen Localization And Segmentation Using Machine Learning And 3D Active Contours.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2018
Automated segmentation of the spleen in CT volumes is difficult due to variations in size, shape, and position of the spleen within the abdominal cavity as well as similarity of intensity values among organs in the abdominal cavity. In this paper we ...
Imaging, Three-Dimensional Abdomen Spleen Humans Algorithms Thorax Machine Learning Tomography, X-Ray Computed
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Automatic thoracic anatomy segmentation on CT images using hierarchical fuzzy models and registration.

Medical physics Mar 1, 2016
PURPOSE: In an attempt to overcome several hurdles that exist in organ segmentation approaches, the authors previously described a general automatic anatomy recognition (AAR) methodology for segmenting all major organs in multiple body regions body-w...
Automation Tomography, X-Ray Computed Pattern Recognition, Automated Humans Image Processing, Computer-Assisted Thorax Radiography, Thoracic Algorithms Fuzzy Logic
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