Coarse-grained models have provided researchers with greatly improved computational efficiency in modeling structures and dynamics of biomacromolecules, but, to be practically useful, they need fast and accurate conversion methods back to the all-ato...
Efficient prediction of blastocyst formation from early-stage human embryos is imperative for improving the success rates of assisted reproductive technology (ART). Clinics transfer embryos at the blastocyst stage on Day-5 but Day-3 embryo transfer o...
The performance gains achieved by deep learning models nowadays are mainly attributed to the usage of ever larger datasets. In this study, we present and contrast the performance gains that can be achieved via accessing larger high-quality datasets v...
Standard-of-care (SoC) imaging for assessing colorectal polyps during colonoscopy, based on white-light colonoscopy (WLC) and narrow-band imaging (NBI), does not have sufficient accuracy to assess the invasion depth of complex polyps non-invasively d...
Can brain structure predict human intelligence? T1-weighted structural brain magnetic resonance images (sMRI) have been correlated with intelligence. However, the population-level association does not fully account for individual variability in intel...
Artificial intelligence (AI) based treatment planning tools are being implemented in clinic. However, human interactions with such AI tools are rarely analyzed. This study aims to comprehend human planner's interaction with the AI planning tool and i...
Deep learning is increasingly permeating neuroscience, leading to a rise in signal-processing applications for extracellular recordings. These signals capture the activity of small neuronal populations, necessitating 'spike sorting' to assign action ...
Journal of computer assisted tomography
Nov 13, 2024
OBJECTIVE: This preliminary study aims to assess the image quality of enhanced-resolution deep learning reconstruction (ER-DLR) in magnetic resonance cholangiopancreatography (MRCP) and compare it with non-ER-DLR MRCP images.
OBJECTIVE: To assess the viability of using ultra-low radiation and contrast medium (CM) dosage in aortic computed tomography angiography (CTA) through the application of low tube voltage (60kVp) and a novel deep learning image reconstruction algorit...
RATIONALE AND OBJECTIVES: The early prediction of response to neoadjuvant chemotherapy (NAC) will aid in the development of personalized treatments for patients with breast cancer. This study investigated the value of longitudinal multimodal deep lea...
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