A 43-year-old male Bell 214C helicopter pilot presented to the emergency ward with flu-like syndrome. His nasopharyngeal severe acute respiratory syndrome coronavirus 2 real-time polymerase chain reaction test was positive, and a chest computed tomog...
Magnetic Resonance Imaging (MRI) has been widely used to acquire structural and functional information about the brain. In a group- or voxel-wise analysis, it is essential to correct the bias field of the radiofrequency coil and to extract the brain ...
European journal of nuclear medicine and molecular imaging
May 19, 2022
PURPOSE: This work attempts to decode the discriminative information in dopamine transporter (DAT) imaging using deep learning for the differential diagnosis of parkinsonism.
With the rapid growth of multimedia data on the Internet, there has been a rapid rise in the demand for visual-textual cross-media retrieval between images and sentences. However, the heterogeneous property of visual and textual data brings huge chal...
Image classification is probably the most fundamental task in radiology artificial intelligence. To reduce the burden of acquiring and labeling data sets, we employed a two-pronged strategy. We automatically extracted labels from radiology reports in...
The accumulation of multisite large-sample MRI datasets collected during large brain research projects in the last decade has provided critical resources for understanding the neurobiological mechanisms underlying cognitive functions and brain disord...
Mobile microrobots hold remarkable potential to revolutionize health care by enabling unprecedented active medical interventions and theranostics, such as active cargo delivery and microsurgical manipulations in hard-to-reach body sites. High-resolut...
Many real-world mission-critical applications require continual online learning from noisy data and real-time decision making with a defined confidence level. Brain-inspired probabilistic models of neural network can explicitly handle the uncertainty...
Functional neural activities manifest geometric patterns, as evidenced by the evolving network topology of functional connectivities (FC) even in the resting state. In this work, we propose a novel manifold-based geometric neural network for function...
This work aimed to investigate the brain resting-state functional magnetic resonance imaging (fMRI) technology based on the depth autoencoders algorithm and to evaluate the clinically curative effect of pregabalin in the treatment of postherpetic neu...
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