Environmental pollution (Barking, Essex : 1987)
Jun 6, 2021
Airborne hyperspectral remote sensing has the characteristics of high spatial and spectral resolutions, and provides an opportunity for accurate and efficient inland water qauality monitoring. Many studies have focused on evaluating and quantifying t...
PURPOSE: To develop an end-to-end deep learning technique for nonrigid motion-corrected (MoCo) reconstruction of ninefold undersampled free-breathing whole-heart coronary MRA (CMRA).
Airborne particulate matter (PM) has become a global environmental issue. This PM has harmful effects on public health and precision industries. Conventional air-quality monitoring methods usually utilize expensive equipment, and they are cumbersome ...
The broad possibilities offered by microfluidic devices in relation to massive data monitoring and acquisition open the door to the use of deep learning technologies in a very promising field: cell culture monitoring. In this work, we develop a metho...
BACKGROUND: Differentiating acute bilirubin encephalopathy (ABE) from non-ABE in neonates with hyperbilirubinemia (HB) from routine magnetic resonance imaging (MRI) is extremely challenging since both conditions demonstrate similar T1 hyperintensitie...
PURPOSE: The purpose of this study was to develop and evaluate an algorithm that can automatically estimate the amount of coronary artery calcium (CAC) from unenhanced electrocardiography (ECG)-gated computed tomography (CT) cardiac volume acquisitio...
PURPOSE: To develop and test the performance of deep convolutional neural networks (DCNNs) for automated classification of age and sex on chest radiographs (CXR).
Computer methods and programs in biomedicine
Jun 5, 2021
BACKGROUND AND OBJECTIVE: Early-stage osteonecrosis of the femoral head (ONFH) can be difficult to detect because of a lack of symptoms. Magnetic resonance imaging (MRI) is sufficiently sensitive to detect ONFH; however, the diagnosis of ONFH require...
Magnetic resonance fingerprinting (MRF) is a quantitative MRI (qMRI) framework that provides simultaneous estimates of multiple relaxation parameters as well as metrics of field inhomogeneity in a single acquisition. However, current challenges exist...
Recent advances in deep learning have led to a promising performance in many medical image analysis tasks. As the most commonly performed radiological exam, chest radiographs are a particularly important modality for which a variety of applications h...
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