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Thorax

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3D Kinect Camera Scheme with Time-Series Deep-Learning Algorithms for Classification and Prediction of Lung Tumor Motility.

Sensors (Basel, Switzerland)
This paper proposes a time-series deep-learning 3D Kinect camera scheme to classify the respiratory phases with a lung tumor and predict the lung tumor displacement. Specifically, the proposed scheme is driven by two time-series deep-learning algorit...

Accurate auto-labeling of chest X-ray images based on quantitative similarity to an explainable AI model.

Nature communications
The inability to accurately, efficiently label large, open-access medical imaging datasets limits the widespread implementation of artificial intelligence models in healthcare. There have been few attempts, however, to automate the annotation of such...

H-SegNet: hybrid segmentation network for lung segmentation in chest radiographs using mask region-based convolutional neural network and adaptive closed polyline searching method.

Physics in medicine and biology
Chest x-ray (CXR) is one of the most commonly used imaging techniques for the detection and diagnosis of pulmonary diseases. One critical component in many computer-aided systems, for either detection or diagnosis in digital CXR, is the accurate segm...

Research on Lung Ultrasound Image Classification Based on Compressed Sensing.

Journal of healthcare engineering
Pneumothorax is a common injury in disaster rescue, traffic accidents, and war trauma environments and requires early diagnosis and treatment. The commonly used X-ray, CT, and other diagnostic instruments are not suitable for rescue sites due to thei...

Comparison and verification of two deep learning models for the detection of chest CT rib fractures.

Acta radiologica (Stockholm, Sweden : 1987)
BACKGROUND: A high false-positive rate remains a technical glitch hindering the broad spectrum of application of deep-learning-based diagnostic tools in routine radiological practice from assisting in diagnosing rib fractures.

A clinical evaluation study of cardiothoracic ratio measurement using artificial intelligence.

BMC medical imaging
BACKGROUND: Artificial intelligence, particularly the deep learning (DL) model, can provide reliable results for automated cardiothoracic ratio (CTR) measurement on chest X-ray (CXR) images. In everyday clinical use, however, this technology is usual...

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

Sensors (Basel, Switzerland)
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...

A regularization method to improve adversarial robustness of neural networks for ECG signal classification.

Computers in biology and medicine
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...

Vulture-Based AdaBoost-Feedforward Neural Frame Work for COVID-19 Prediction and Severity Analysis System.

Interdisciplinary sciences, computational life sciences
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...