AIMC Topic: Liver

Clear Filters Showing 331 to 340 of 589 articles

A study of using a deep learning image reconstruction to improve the image quality of extremely low-dose contrast-enhanced abdominal CT for patients with hepatic lesions.

The British journal of radiology Dec 11, 2020
OBJECTIVE: To investigate the feasibility of using deep learning image reconstruction (DLIR) to significantly reduce radiation dose and improve image quality in contrast-enhanced abdominal CT.
Aged Aged, 80 and over Adult Male Tomography, X-Ray Computed Female Humans Reproducibility of Results Prospective Studies Liver Radiographic Image Interpretation, Computer-Assisted Radiation Dosage Radiographic Image Enhancement Middle Aged Deep Learning Liver Neoplasms Contrast Media
View on PubMed DOI

A large-scale internal validation study of unsupervised virtual trichrome staining technologies on nonalcoholic steatohepatitis liver biopsies.

Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc Dec 9, 2020
Non-alcoholic steatohepatitis (NASH) is a fatty liver disease characterized by accumulation of fat in hepatocytes with concurrent inflammation and is associated with morbidity, cirrhosis and liver failure. After extraction of a liver core biopsy, tis...
Clinical Decision-Making Female Reproducibility of Results Aged Software Decision Support Techniques Retrospective Studies Middle Aged Severity of Illness Index Adolescent Child Aged, 80 and over Young Adult Adult Male Humans Neural Networks, Computer Microscopy Staining and Labeling Predictive Value of Tests Azo Compounds Liver Cirrhosis Hematoxylin Biopsy Image Interpretation, Computer-Assisted Liver Methyl Green Eosine Yellowish-(YS) Non-alcoholic Fatty Liver Disease Coloring Agents
View on PubMed DOI

Displacement Estimation in Ultrasound Elastography Using Pyramidal Convolutional Neural Network.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control Nov 24, 2020
In this article, two novel deep learning methods are proposed for displacement estimation in ultrasound elastography (USE). Although convolutional neural networks (CNNs) have been very successful for displacement estimation in computer vision, they h...
Humans Deep Learning Image Processing, Computer-Assisted Liver Phantoms, Imaging Elasticity Imaging Techniques
View on PubMed DOI

Toward reliable automatic liver and tumor segmentation using convolutional neural network based on 2.5D models.

International journal of computer assisted radiology and surgery Nov 21, 2020
PURPOSE: We investigated the parameter configuration in the automatic liver and tumor segmentation using a convolutional neural network based on 2.5D model. The implementation of 2.5D model shows promising results since it allows the network to have ...
Neural Networks, Computer Liver Neoplasms Image Processing, Computer-Assisted Models, Theoretical Liver Humans
View on PubMed DOI

Fully automated prediction of liver fibrosis using deep learning analysis of gadoxetic acid-enhanced MRI.

European radiology Nov 17, 2020
OBJECTIVES: To (1) develop a fully automated deep learning (DL) algorithm based on gadoxetic acid-enhanced hepatobiliary phase (HBP) MRI and (2) compare the diagnostic performance of DL vs. MR elastography (MRE) for noninvasive staging of liver fibro...
Retrospective Studies Middle Aged Deep Learning Liver Cirrhosis Magnetic Resonance Imaging Humans Liver Gadolinium DTPA Elasticity Imaging Techniques
View on PubMed DOI

CT-ORG, a new dataset for multiple organ segmentation in computed tomography.

Scientific data Nov 11, 2020
Despite the relative ease of locating organs in the human body, automated organ segmentation has been hindered by the scarcity of labeled training data. Due to the tedium of labeling organ boundaries, most datasets are limited to either a small numbe...
Humans Urinary Bladder Neural Networks, Computer Fourier Analysis Algorithms Image Processing, Computer-Assisted Tomography, X-Ray Computed Brain Kidney Lung Liver Imaging, Three-Dimensional Bone and Bones
View on PubMed DOI

Deep learning-enabled multi-organ segmentation in whole-body mouse scans.

Nature communications Nov 6, 2020
Whole-body imaging of mice is a key source of information for research. Organ segmentation is a prerequisite for quantitative analysis but is a tedious and error-prone task if done manually. Here, we present a deep learning solution called AIMOS that...
Algorithms Brain Spleen X-Ray Microtomography Mice Lung Female Whole Body Imaging Kidney Deep Learning Reproducibility of Results Animal Structures Mice, Inbred C57BL Image Processing, Computer-Assisted Animals Liver Male
View on PubMed DOI

Identification of early liver toxicity gene biomarkers using comparative supervised machine learning.

Scientific reports Nov 5, 2020
Screening agrochemicals and pharmaceuticals for potential liver toxicity is required for regulatory approval and is an expensive and time-consuming process. The identification and utilization of early exposure gene signatures and robust predictive mo...
Gene Expression Regulation Oligonucleotide Array Sequence Analysis Chemical and Drug Induced Liver Injury Agrochemicals Liver Genetic Markers Supervised Machine Learning Algorithms Animals Male Rats
View on PubMed DOI

Fully-automated functional region annotation of liver via a 2.5D class-aware deep neural network with spatial adaptation.

Computer methods and programs in biomedicine Nov 4, 2020
BACKGROUND AND OBJECTIVE: Automatic functional region annotation of liver should be very useful for preoperative planning of liver resection in the clinical domain. However, many traditional computer-aided annotation methods based on anatomical landm...
Image Processing, Computer-Assisted Neural Networks, Computer Liver Algorithms Tomography, X-Ray Computed
View on PubMed DOI

Layer Embedding Analysis in Convolutional Neural Networks for Improved Probability Calibration and Classification.

IEEE transactions on medical imaging Oct 28, 2020
In this project, our goal is to develop a method for interpreting how a neural network makes layer-by-layer embedded decisions when trained for a classification task, and also to use this insight for improving the model performance. To do this, we fi...
Liver Humans Neural Networks, Computer Probability Imaging, Three-Dimensional Calibration
View on PubMed DOI
Popular Topics
Recent Journals