Previous studies have shown that functional mobility, along with other physical functions, decreases with advanced age. However, it is still unclear which domains of functioning (body structures, body functions, and activities) are most closely relat...
Emotion states recognition using wireless signals is an emerging area of research that has an impact on neuroscientific studies of human behaviour and well-being monitoring. Currently, standoff emotion detection is mostly reliant on the analysis of f...
Modern neurophysiology research requires the interrogation of high-dimensionality data sets. Machine learning and artificial intelligence (ML/AI) workflows have permeated into nearly all aspects of daily life in the developed world but have not been ...
BACKGROUND: Surface-guided radiation therapy can be used to continuously monitor a patient's surface motions during radiotherapy by a non-irradiating, noninvasive optical surface imaging technique. In this study, machine learning methods were applied...
Due to the inter- and intra- variation of respiratory motion, it is highly desired to provide real-time volumetric images during the treatment delivery of lung stereotactic body radiation therapy (SBRT) for accurate and active motion management. In t...
Motion compensation can eliminate inconsistencies of respiratory movement during image acquisitions for precise vascular reconstruction in the clinical diagnosis of vascular disease from x-ray angiographic image sequences. In x-ray-based vascular int...
The aim of this study was to develop a deep neural network for respiratory motion compensation in free-breathing cine MRI and evaluate its performance. An adversarial autoencoder network was trained using unpaired training data from healthy volunteer...
Rapid assessment of breathing patterns is important for several emergency medical situations. In this research, we developed a non-invasive breathing analysis system that automatically detects different types of breathing patterns of clinical signifi...
Respiration-induced B fluctuation corrupts MRI images by inducing phase errors in k-space. A few approaches such as navigator have been proposed to correct for the artifacts at the expense of sequence modification. In this study, a new deep learning ...
To improve the prediction accuracy of respiratory signals by adapting the multi-layer perceptron neural network (MLP-NN) model to changing respiratory signals. We have previously developed an MLP-NN to predict respiratory signals obtained from a real...
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