AIMC Topic: Iohexol
Clear Filters Showing 1 to 10 of 11 articles
Low-iodine-dose computed tomography coupled with an artificial intelligence-based contrast-boosting technique in children: a retrospective study on comparison with conventional-iodine-dose computed tomography.
Pediatric radiology
Jun 5, 2024
BACKGROUND: Low-iodine-dose computed tomography (CT) protocols have emerged to mitigate the risks associated with contrast injection, often resulting in decreased image quality.
Deep learning reconstruction allows for usage of contrast agent of lower concentration for coronary CTA than filtered back projection and hybrid iterative reconstruction.
Acta radiologica (Stockholm, Sweden : 1987)
Aug 17, 2022
BACKGROUND: The demand for homogeneous and higher vascular contrast enhancement is critical to provide an appropriate interpretation of abnormal vascular findings in coronary computed tomography angiography (CTA).
A comparison of the fusion model of deep learning neural networks with human observation for lung nodule detection and classification.
The British journal of radiology
Jun 11, 2021
OBJECTIVES: To compare the diagnostic performance of a newly developed artificial intelligence (AI) algorithm derived from the fusion of convolution neural networks (CNN) versus human observers in the estimation of malignancy risk in pulmonary nodule...
Image Quality Assessment of Abdominal CT by Use of New Deep Learning Image Reconstruction: Initial Experience.
AJR. American journal of roentgenology
Apr 14, 2020
The purpose of this study was to perform quantitative and qualitative evaluation of a deep learning image reconstruction (DLIR) algorithm in contrast-enhanced oncologic CT of the abdomen. Retrospective review (April-May 2019) of the cases of adults...
Multiphase CT-based prediction of Child-Pugh classification: a machine learning approach.
European radiology experimental
Apr 6, 2020
BACKGROUND: To evaluate whether machine learning algorithms allow the prediction of Child-Pugh classification on clinical multiphase computed tomography (CT).
Ultra-Low-Dose Neck CT With Low-Dose Contrast Material for Preoperative Staging of Thyroid Cancer: Image Quality and Diagnostic Performance.
AJR. American journal of roentgenology
Dec 17, 2018
OBJECTIVE: Although CT has been used as a complementary diagnostic method for the preoperative diagnosis of thyroid cancer, it has the shortcomings of substantial radiation exposure and the use of contrast material (CM). The purpose of this article i...
Novel Breast Imaging and Machine Learning: Predicting Breast Lesion Malignancy at Cone-Beam CT Using Machine Learning Techniques.
AJR. American journal of roentgenology
May 24, 2018
OBJECTIVE: The purpose of this study is to evaluate the diagnostic performance of machine learning techniques for malignancy prediction at breast cone-beam CT (CBCT) and to compare them to human readers.
Deep learning analysis of the myocardium in coronary CT angiography for identification of patients with functionally significant coronary artery stenosis.
Medical image analysis
Nov 26, 2017
In patients with coronary artery stenoses of intermediate severity, the functional significance needs to be determined. Fractional flow reserve (FFR) measurement, performed during invasive coronary angiography (ICA), is most often used in clinical pr...
Selection of peripheral intravenous catheters with 24-gauge side-holes versus those with 22-gauge end-hole for MDCT: A prospective randomized study.
European journal of radiology
Dec 6, 2016
PURPOSE: To compare the 24-gauge side-holes catheter and conventional 22-gauge end-hole catheter in terms of safety, injection pressure, and contrast enhancement on multi-detector computed tomography (MDCT).
A Machine Learning Approach to Estimate the Glomerular Filtration Rate in Intensive Care Unit Patients Based on Plasma Iohexol Concentrations and Covariates.
Clinical pharmacokinetics
Feb 1, 2021
OBJECTIVE: This work aims to evaluate whether a machine learning approach is appropriate to estimate the glomerular filtration rate in intensive care unit patients based on sparse iohexol pharmacokinetic data and a limited number of predictors.
Don't Miss the Future of Medicine
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.
Subscribe NowPopular Topics
- Machine Learning 30978
- Neural Networks, Computer 29696
- Algorithms 26813
- Deep Learning 26324
- Artificial Intelligence 24267
- Robotics 13307
- Image Processing, Computer-Assisted 9512
- Retrospective Studies 9097
- Magnetic Resonance Imaging 6173
- Reproducibility of Results 5589
- Tomography, X-Ray Computed 4765
- Support Vector Machine 4678
- Computational Biology 4229
- Brain 4045
- Computer Simulation 3877
Recent Journals
- Scientific reports 5865
- Sensors (Basel, Switzerland) 4794
- PloS one 4011
- Neural networks : the official journal of the International Neural Network Society 2928
- Computational intelligence and neuroscience 1931
- Computers in biology and medicine 1839
- Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference 1686
- Studies in health technology and informatics 1278
- IEEE journal of biomedical and health informatics 1129
- Journal of chemical information and modeling 994
- Nature communications 938
- Computer methods and programs in biomedicine 883
- Bioinformatics (Oxford, England) 861
- Briefings in bioinformatics 850
- IEEE transactions on neural networks and learning systems 823