Computer methods and programs in biomedicine
Feb 15, 2021
BACKGROUND AND OBJECTIVE: Diabetes is a chronic pathology which is affecting more and more people over the years. It gives rise to a large number of deaths each year. Furthermore, many people living with the disease do not realize the seriousness of ...
PURPOSE: To introduce a novel deep learning (DL) T2-weighted TSE imaging (T2) sequence in prostate MRI and investigate its impact on examination time, image quality, diagnostic confidence, and PI-RADS classification compared to standard T2-weighted T...
Exponential growth of biomedical literature and clinical data demands more robust yet precise computational methodologies to extract useful insights from biomedical literature and to perform accurate assignment of disease-specific codes. Such approac...
The international journal of medical robotics + computer assisted surgery : MRCAS
Feb 15, 2021
BACKGROUND: Two-dimensional (2D)-3D registration is challenging in the presence of implant projections on intraoperative images, which can limit the registration capture range. Here, we investigate the use of deep-learning-based inpainting for removi...
Particle identification and selection, which is a prerequisite for high-resolution structure determination of biological macromolecules via single-particle cryo-electron microscopy poses a major bottleneck for automating the steps of structure determ...
BACKGROUND: Image segmentation is a common task in medical imaging e.g., for volumetry analysis in cardiac MRI. Artificial neural networks are used to automate this task with performance similar to manual operators. However, this performance is only ...
Artificial intelligence (AI) is a new frontier and often enigmatic for medical professionals. Cloud computing could open up the field of computer vision to a wider medical audience and deep learning on the cloud allows one to design, develop, train a...
PURPOSE: Alzheimer's disease (AD) is a progressive and irreversible neurodegenerative disease. In recent years, machine learning methods have been widely used on analysis of neuroimage for quantitative evaluation and computer-aided diagnosis of AD or...
Journal of magnetic resonance (San Diego, Calif. : 1997)
Feb 13, 2021
The applicability of generative adversarial networks (GANs) capable of unsupervised anomaly detection (AnoGAN) was investigated in the management of quality of H-MRS human brain spectra at 3.0 T. The AnoGAN was trained in an unsupervised manner solel...
Infections with pathogenic bacteria entering the mammary gland through the teat canal are the most common cause of mastitis in dairy cows; therefore, sustaining the integrity of the teat canal and its adjacent tissues is critical to resist infection....
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