AIMC Topic: Contrast Media

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Plaque components segmentation in carotid artery on simultaneous non-contrast angiography and intraplaque hemorrhage imaging using machine learning.

Magnetic resonance imaging Apr 5, 2019
PURPOSE: This study sought to determine the feasibility of using Simultaneous Non-contrast Angiography and intraPlaque Hemorrhage (SNAP) to detect the lipid-rich/necrotic core (LRNC), and develop a machine learning based algorithm to segment plaque c...
Sensitivity and Specificity Male Middle Aged Contrast Media Calcinosis Machine Learning Algorithms Female Reproducibility of Results Aged Plaque, Atherosclerotic Angiography Necrosis Carotid Stenosis Plaque, Amyloid Lipids Cerebral Hemorrhage Bayes Theorem Carotid Arteries Carotid Artery, Common Humans
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Detection and characterization of MRI breast lesions using deep learning.

Diagnostic and interventional imaging Mar 26, 2019
PURPOSE: The purpose of this study was to assess the potential of a deep learning model to discriminate between benign and malignant breast lesions using magnetic resonance imaging (MRI) and characterize different histological subtypes of breast lesi...
Algorithms Female Breast Neoplasms Deep Learning Contrast Media Magnetic Resonance Imaging Humans Breast Datasets as Topic Gadolinium
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DeepCEST: 9.4 T Chemical exchange saturation transfer MRI contrast predicted from 3 T data - a proof of concept study.

Magnetic resonance in medicine Feb 25, 2019
PURPOSE: To determine the feasibility of employing the prior knowledge of well-separated chemical exchange saturation transfer (CEST) signals in the 9.4 T Z-spectrum to separate overlapping CEST signals acquired at 3 T, using a deep learning approach...
Imaging, Three-Dimensional Contrast Media Magnetic Resonance Imaging Image Interpretation, Computer-Assisted Proof of Concept Study Humans Neural Networks, Computer Brain Brain Neoplasms
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Automated selection of myocardial inversion time with a convolutional neural network: Spatial temporal ensemble myocardium inversion network (STEMI-NET).

Magnetic resonance in medicine Feb 3, 2019
PURPOSE: Delayed enhancement imaging is an essential component of cardiac MRI, which is used widely for the evaluation of myocardial scar and viability. The selection of an optimal inversion time (TI) or null point (TI ) to suppress the background my...
Contrast Media Magnetic Resonance Imaging Myocardium Heart Pattern Recognition, Automated Middle Aged Adolescent Child Image Processing, Computer-Assisted Gadolinium Humans Neural Networks, Computer Algorithms Retrospective Studies Female Aged Aged, 80 and over Young Adult Adult Male
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Intracranial Vessel Wall Segmentation Using Convolutional Neural Networks.

IEEE transactions on bio-medical engineering Feb 1, 2019
OBJECTIVE: To develop an automated vessel wall segmentation method using convolutional neural networks to facilitate the quantification on magnetic resonance (MR) vessel wall images of patients with intracranial atherosclerotic disease (ICAD).
Image Interpretation, Computer-Assisted Automation Magnetic Resonance Angiography Middle Cerebral Artery Intracranial Arteriosclerosis Male Humans Middle Aged Neural Networks, Computer Imaging, Three-Dimensional Retrospective Studies Contrast Media Female Risk Factors
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A Comparative Texture Analysis Based on NECT and CECT Images to Differentiate Lung Adenocarcinoma from Squamous Cell Carcinoma.

Journal of medical systems Feb 1, 2019
The purpose of the study was to compare the texture based discriminative performances between non-contrast enhanced computed tomography (NECT) and contrast-enhanced computed tomography (CECT) images in differentiating lung adenocarcinoma (ADC) from s...
Carcinoma, Squamous Cell Aged Aged, 80 and over Adult Male Humans Retrospective Studies Tomography, X-Ray Computed Female Middle Aged Image Processing, Computer-Assisted Lung Neoplasms Socioeconomic Factors Support Vector Machine Contrast Media Diagnosis, Differential Adenocarcinoma of Lung
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Automated Segmentation of Colorectal Tumor in 3D MRI Using 3D Multiscale Densely Connected Convolutional Neural Network.

Journal of healthcare engineering Jan 31, 2019
The main goal of this work is to automatically segment colorectal tumors in 3D T2-weighted (T2w) MRI with reasonable accuracy. For such a purpose, a novel deep learning-based algorithm suited for volumetric colorectal tumor segmentation is proposed. ...
Contrast Media Magnetic Resonance Imaging Humans Colorectal Neoplasms False Positive Reactions Neural Networks, Computer Deep Learning Intestine, Large Algorithms Imaging, Three-Dimensional Image Processing, Computer-Assisted
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A clinical, proteomics, and artificial intelligence-driven model to predict acute kidney injury in patients undergoing coronary angiography.

Clinical cardiology Jan 8, 2019
BACKGROUND: Standard measures of kidney function are only modestly useful for accurate prediction of risk for acute kidney injury (AKI).
Artificial Intelligence Prospective Studies Biomarkers Acute Kidney Injury Female Aged Male Risk Assessment Creatinine Incidence ROC Curve Proteomics Contrast Media Humans Predictive Value of Tests Coronary Angiography Coronary Artery Disease
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Radiogenomics in Clear Cell Renal Cell Carcinoma: Machine Learning-Based High-Dimensional Quantitative CT Texture Analysis in Predicting PBRM1 Mutation Status.

AJR. American journal of roentgenology Jan 2, 2019
OBJECTIVE: The purpose of this study is to evaluate the potential value of machine learning (ML)-based high-dimensional quantitative CT texture analysis in predicting the mutation status of the gene encoding the protein polybromo-1 (PBRM1) in patient...
Radiographic Image Interpretation, Computer-Assisted DNA-Binding Proteins Kidney Neoplasms Carcinoma, Renal Cell Transcription Factors Humans Contrast Media Predictive Value of Tests Mutation Reproducibility of Results Aged Male Middle Aged Nuclear Proteins Machine Learning Algorithms Retrospective Studies Tomography, X-Ray Computed Female
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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...
Thyroid Neoplasms Radiation Dosage Contrast Media Humans Aged Neoplasm Staging Retrospective Studies Signal-To-Noise Ratio Radiographic Image Interpretation, Computer-Assisted Tomography, X-Ray Computed Adult Iohexol Male Female Middle Aged Thyroidectomy
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