IEEE journal of biomedical and health informatics
Jul 9, 2019
Given the complicated relationship between the magnetic resonance imaging (MRI) signals and the attenuation values, the attenuation correction in hybrid positron emission tomography (PET)/MRI systems remains a challenging task. Currently, existing me...
Advanced materials (Deerfield Beach, Fla.)
Jul 9, 2019
Artificial intelligence (AI) and nanotechnology are two fields that are instrumental in realizing the goal of precision medicine-tailoring the best treatment for each cancer patient. Recent conversion between these two fields is enabling better patie...
Even though the majority of population studies in environmental health focus on a single factor, environmental exposure in the real world is a mixture of many chemicals. The concept of "exposome" leads to an intellectual framework of measuring many e...
Digital reconstruction or tracing of 3D neuron is essential for understanding the brain functions. While existing automatic tracing algorithms work well for the clean neuronal image with a single neuron, they are not robust to trace the neuron surrou...
Current problems in diagnostic radiology
Jul 9, 2019
Convolutional neural networks have been shown to demonstrate high diagnostic performance in radiologic image interpretation tasks ranging from recognition of acute stroke on computed tomography to identification of tuberculosis on plain radiographs. ...
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Jul 9, 2019
Compressed sensing (CS) theory can accelerate multi-contrast magnetic resonance imaging (MRI) by sampling fewer measurements within each contrast. However, conventional optimization-based reconstruction models suffer several limitations, including a ...
During process development, the experimental search space is defined by the number of experiments that can be performed in specific time frames but also by its sophistication (e.g., inputs, sensors, sampling frequency, analytics). High-throughput liq...
BACKGROUND: Machine learning (ML) has been increasingly used in medicine and neurosurgery. We sought to determine whether ML models can distinguish ruptured from unruptured aneurysms and identify features associated with rupture.
Previous lesion behavior studies primarily used univariate lesion behavior mapping techniques to map the anatomical basis of spatial neglect after right brain damage. These studies led to inconsistent results and lively controversies. Given these inc...
International journal of computer assisted radiology and surgery
Jul 9, 2019
PURPOSE: Current manual catheters for transbronchial biopsy in the lung lack a steering ability, which hampers a physician's ability to reach nodules in the peripheral lung. The objective of this paper is to design and build a multisection robot with...
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