AIMC Topic: Thorax

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Deep Learning-Based Computer-Aided Pneumothorax Detection Using Chest X-ray Images.

Sensors (Basel, Switzerland) Mar 15, 2022
Pneumothorax is a thoracic disease leading to failure of the respiratory system, cardiac arrest, or in extreme cases, death. Chest X-ray (CXR) imaging is the primary diagnostic imaging technique for the diagnosis of pneumothorax. A computerized diagn...
Humans Thorax X-Rays Pneumothorax Computers Deep Learning
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A regularization method to improve adversarial robustness of neural networks for ECG signal classification.

Computers in biology and medicine Feb 24, 2022
With the advancement of machine leaning technologies, Deep Neural Networks (DNNs) have been utilized for automated interpretation of Electrocardiogram (ECG) signals to identify potential abnormalities in a patient's heart within a second. Studies hav...
Humans Electrocardiography Thorax Neural Networks, Computer
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Vulture-Based AdaBoost-Feedforward Neural Frame Work for COVID-19 Prediction and Severity Analysis System.

Interdisciplinary sciences, computational life sciences Feb 22, 2022
In today's scenario, many scientists and medical researchers have been involved in deep research for discovering the desired medicine to reduce the spread of COVID-19 disease. However, still, it is not the end. Hence, predicting the COVID possibility...
Deep Learning Thorax COVID-19 SARS-CoV-2 Humans Machine Learning
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Using Radiomics as Prior Knowledge for Thorax Disease Classification and Localization in Chest X-rays.

AMIA ... Annual Symposium proceedings. AMIA Symposium Feb 21, 2022
Chest X-ray becomes one of the most common medical diagnoses due to its noninvasiveness. The number of chest X-ray images has skyrocketed, but reading chest X-rays still have been manually performed by radiologists, which creates huge burnouts and de...
Thorax Radiography X-Rays Humans Lung Diseases Deep Learning
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Automatic contouring of normal tissues with deep learning for preclinical radiation studies.

Physics in medicine and biology Feb 9, 2022
Delineation of relevant normal tissues is a bottleneck in image-guided precision radiotherapy workflows for small animals. A deep learning (DL) model for automatic contouring using standardized 3D micro cone-beam CT (CBCT) volumes as input is propose...
Thorax Organs at Risk Radiotherapy Planning, Computer-Assisted Animals Cone-Beam Computed Tomography Lung Image Processing, Computer-Assisted Deep Learning
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Deep learning-based segmentation of the thorax in mouse micro-CT scans.

Scientific reports Feb 2, 2022
For image-guided small animal irradiations, the whole workflow of imaging, organ contouring, irradiation planning, and delivery is typically performed in a single session requiring continuous administration of anaesthetic agents. Automating contourin...
Thorax X-Ray Microtomography Radiographic Image Interpretation, Computer-Assisted Workflow Reproducibility of Results Observer Variation Animals Radiography, Thoracic Female Mice, Inbred BALB C Predictive Value of Tests Deep Learning Mice
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Effective deep learning approaches for predicting COVID-19 outcomes from chest computed tomography volumes.

Scientific reports Feb 2, 2022
The rapid evolution of the novel coronavirus disease (COVID-19) pandemic has resulted in an urgent need for effective clinical tools to reduce transmission and manage severe illness. Numerous teams are quickly developing artificial intelligence appro...
Humans COVID-19 Tomography, X-Ray Computed SARS-CoV-2 Deep Learning Algorithms Prognosis Image Interpretation, Computer-Assisted Thorax Image Processing, Computer-Assisted Databases, Genetic
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E-TBNet: Light Deep Neural Network for Automatic Detection of Tuberculosis with X-ray DR Imaging.

Sensors (Basel, Switzerland) Jan 21, 2022
Currently, the tuberculosis (TB) detection model based on chest X-ray images has the problem of excessive reliance on hardware computing resources, high equipment performance requirements, and being harder to deploy in low-cost personal computer and ...
Thorax X-Rays Radiography Tuberculosis Humans Neural Networks, Computer
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Objective evaluation of deep uncertainty predictions for COVID-19 detection.

Scientific reports Jan 17, 2022
Deep neural networks (DNNs) have been widely applied for detecting COVID-19 in medical images. Existing studies mainly apply transfer learning and other data representation strategies to generate accurate point estimates. The generalization power of ...
Deep Learning Humans Thorax COVID-19
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Detection of COVID-19 With CT Images Using Hybrid Complex Shearlet Scattering Networks.

IEEE journal of biomedical and health informatics Jan 17, 2022
With the ongoing worldwide coronavirus disease 2019 (COVID-19) pandemic, it is desirable to develop effective algorithms to automatically detect COVID-19 with chest computed tomography (CT) images. Recently, a considerable number of methods based on ...
Thorax Humans SARS-CoV-2 COVID-19 Deep Learning Tomography, X-Ray Computed
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