PURPOSE: To develop a deep convolutional neural network (CNN) model to categorize multiphase CT and MRI liver observations using the liver imaging reporting and data system (LI-RADS) (version 2014).
Artificial intelligence (AI), particularly deep learning algorithms, is gaining extensive attention for its excellent performance in image-recognition tasks. They can automatically make a quantitative assessment of complex medical image characteristi...
Journal of X-ray science and technology
Jan 1, 2019
OBJECTIVE: To develop and test a novel method for automatic quantification of hepatic steatosis in histologic images based on the deep learning scheme designed to predict the fat ratio directly, which aims to improve accuracy in diagnosis of non-alco...
Accurate segmentation of specific organ from computed tomography (CT) scans is a basic and crucial task for accurate diagnosis and treatment. To avoid time-consuming manual optimization and to help physicians distinguish diseases, an automatic organ ...
CONTEXT: The importance of phytochemicals/natural products as potential therapeutic agents in the present context is gaining a lot of importance. India with a rich heritage of such preparations needs evaluation as potent drugs. Explant culture system...
Journal of special operations medicine : a peer reviewed journal for SOF medical professionals
Jan 1, 2018
During routine aircraft start-up procedures at a US Naval Air Station, an aviation mishap occurred, resulting in the pilot suffering a traumatic brain injury and the copilot acquiring bilateral hemopneumothoraces, a ruptured diaphragm, and hepatic an...
Zhonghua gan zang bing za zhi = Zhonghua ganzangbing zazhi = Chinese journal of hepatology
Dec 20, 2017
To investigate the effects of Lactobacillus paracasei N1115 combined with fructooligosaccharides (FOS) on non-alcoholic fatty liver disease (NAFLD) in mice and its possible mechanism. A total of 50 male C57 mice were randomly and equally divided in...
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