BACKGROUND: To develop an end-to-end deep learning method for automated quantitative assessment of pediatric blunt hepatic trauma based on contrast-enhanced computed tomography (CT).
We evaluated the effectiveness of automated segmentation of the liver and its vessels with a convolutional neural network on non-contrast T1 vibe Dixon acquisitions. A dataset of non-contrast T1 vibe Dixon liver magnetic resonance images was labelled...
Journal of vascular and interventional radiology : JVIR
Dec 16, 2022
PURPOSE: To investigate the utility and generalizability of deep learning subtraction angiography (DLSA) for generating synthetic digital subtraction angiography (DSA) images without misalignment artifacts.
PURPOSE: To develop a deep learning-based method for rapid liver proton-density fat fraction (PDFF) and R * quantification with built-in uncertainty estimation using self-gated free-breathing stack-of-radial MRI.
AIMS: The timely diagnosis of different stages in NAFLD is crucial for disease treatment and reversal. We used hepatocellular ballooning to determine different NAFLD stages.
Non-alcoholic fatty liver disease (NAFLD) affects about 24% of the world's population. Progression of early stages of NAFLD can lead to the more advanced form non-alcoholic steatohepatitis (NASH), and ultimately to cirrhosis or liver cancer. The curr...
Laparoscopic surgery is widely used for treating intra-abdominal conditions involving the gallbladder, pancreas, liver, intestines and reproductive organs. Conventional laparoscopy instruments used in manual surgeries usually have straight shafts and...
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