Computational and mathematical methods in medicine
Oct 8, 2021
Accurate segmentation of liver images is an essential step in liver disease diagnosis, treatment planning, and prognosis. In recent years, although liver segmentation methods based on 2D convolutional neural networks have achieved good results, there...
International journal of molecular sciences
Oct 5, 2021
Bisphenols are important environmental pollutants that are extensively studied due to different detrimental effects, while the molecular mechanisms behind these effects are less well understood. Like other environmental pollutants, bisphenols are bei...
PURPOSE: Volumetric and health assessment of the liver is crucial to avoid poor post-operative outcomes following liver resection surgery. No current methods allow for concurrent and accurate measurement of both Couinaud segmental volumes for future ...
BACKGROUND: To estimate median liver iron concentration (LIC) calculated from magnetic resonance imaging, excluded vessels of the liver parenchyma region were defined manually. Previous works proposed the automated method for excluding vessels from t...
Biological assays are useful in water quality evaluation by providing the overall toxicity of chemical mixtures in environmental waters. However, it is impossible to elucidate the source of toxicity and some lethal combination of pollutants simply us...
The study was designed to determine the impact of acute toxicity of fumaronitrile exposure through tissue damaging, oxidative stress enzymes and histopathological studies in gills, liver and muscle cells of freshwater tilapia fish (Oreochromis mossam...
WD is caused by variants disrupting copper efflux resulting in excessive copper accumulation mainly in liver and brain. The diagnosis of WD is challenged by its variable clinical course, onset, morbidity, and variant type. Currently it is diagnosed...
In vivo bioprinting has recently emerged as a direct fabrication technique to create artificial tissues and medical devices on target sites within the body, enabling advanced clinical strategies. However, existing in vivo bioprinting methods are ofte...
Individualized patient profiling is instrumental for personalized management in hepatocellular carcinoma (HCC). This study built a model based on bidirectional deep neural networks (BiDNNs), an unsupervised machine-learning approach, to integrate mu...
The aim of the study was to use a previously proposed mask region-based convolutional neural network (Mask R-CNN) for automatic abnormal liver density detection and segmentation based on hepatocellular carcinoma (HCC) computed tomography (CT) dataset...
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