AIMC Topic: Contrast Media

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Brain tumor segmentation using 3D Mask R-CNN for dynamic susceptibility contrast enhanced perfusion imaging.

Physics in medicine and biology Sep 18, 2020
The segmentation of neoplasms is an important part of radiotherapy treatment planning, monitoring disease progression, and predicting patient outcome. In the brain, functional magnetic resonance imaging (MRI) like dynamic susceptibility contrast enha...
Humans Imaging, Three-Dimensional Contrast Media Observer Variation Perfusion Imaging Neural Networks, Computer Retrospective Studies Brain Neoplasms
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Machine learning utilising spectral derivative data improves cellular health classification through hyperspectral infra-red spectroscopy.

PloS one Sep 15, 2020
The objective differentiation of facets of cellular metabolism is important for several clinical applications, including accurate definition of tumour boundaries and targeted wound debridement. To this end, spectral biomarkers to differentiate live a...
Principal Component Analysis Necrosis Spectrophotometry, Infrared Contrast Media Cluster Analysis Fibroblasts Humans Machine Learning Image Processing, Computer-Assisted
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Value of MR-based radiomics in differentiating uveal melanoma from other intraocular masses in adults.

European journal of radiology Sep 8, 2020
PURPOSE: To assess the performance of machine learning (ML)-based magnetic resonance imaging (MRI) radiomics analysis for discriminating between uveal melanoma (UM) and other intraocular masses.
Humans Eye Neoplasms Retrospective Studies Image Enhancement Uveal Neoplasms Uveal Melanoma Contrast Media Magnetic Resonance Imaging Diagnosis, Differential Male Middle Aged Adolescent Logistic Models Support Vector Machine Child ROC Curve Aged Young Adult Adult Female Melanoma Reproducibility of Results
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MR Imaging of Endolymphatic Hydrops: Utility of iHYDROPS-Mi2 Combined with Deep Learning Reconstruction Denoising.

Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine Aug 21, 2020
PURPOSE: MRI of endolymphatic hydrops (EH) 4 h after intravenous administration of a single dose of gadolinium-based contrast agent is used for clinical examination in some institutions; however, further improvement in image quality would be valuable...
Humans Deep Learning Endolymphatic Hydrops Endolymph Contrast Media Magnetic Resonance Imaging
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Improving the Reliability of Pharmacokinetic Parameters at Dynamic Contrast-enhanced MRI in Astrocytomas: A Deep Learning Approach.

Radiology Aug 4, 2020
Background Pharmacokinetic (PK) parameters obtained from dynamic contrast agent-enhanced (DCE) MRI evaluates the microcirculation permeability of astrocytomas, but the unreliability from arterial input function (AIF) remains a challenge. Purpose To d...
Reproducibility of Results Brain Neoplasms Male Middle Aged Humans Retrospective Studies Female Astrocytoma Deep Learning Contrast Media Image Enhancement
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Deep learning for cerebral angiography segmentation from non-contrast computed tomography.

PloS one Jul 31, 2020
Cerebral computed tomography angiography is a widely available imaging technique that helps in the diagnosis of vascular pathologies. Contrast administration is needed to accurately assess the arteries. On non-contrast computed tomography, arteries a...
Contrast Media Computed Tomography Angiography Cerebral Angiography Male Deep Learning Image Processing, Computer-Assisted Retrospective Studies Female Humans Brain
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Manual segmentation versus semi-automated segmentation for quantifying vestibular schwannoma volume on MRI.

International journal of computer assisted radiology and surgery Jul 16, 2020
PURPOSE: Management of vestibular schwannoma (VS) is based on tumour size as observed on T1 MRI scans with contrast agent injection. The current clinical practice is to measure the diameter of the tumour in its largest dimension. It has been shown th...
Neuroma, Acoustic Image Processing, Computer-Assisted Contrast Media Magnetic Resonance Imaging Neuroimaging Neurilemmoma Automation Pattern Recognition, Automated Software Algorithms Reproducibility of Results Diagnosis, Computer-Assisted Humans Machine Learning
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Artificial Intelligence and Myocardial Contrast Enhancement Pattern.

Current cardiology reports Jul 7, 2020
PURPOSE OF REVIEW: Machine learning (ML) and deep learning (DL) are two important categories of AI algorithms. Nowadays, AI technology has been gradually applied to cardiac magnetic resonance imaging (CMRI), covering the fields of myocardial contrast...
Heart Contrast Media Magnetic Resonance Imaging Myocardium Humans Artificial Intelligence
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Multiple sclerosis cortical and WM lesion segmentation at 3T MRI: a deep learning method based on FLAIR and MP2RAGE.

NeuroImage. Clinical Jun 30, 2020
The presence of cortical lesions in multiple sclerosis patients has emerged as an important biomarker of the disease. They appear in the earliest stages of the illness and have been shown to correlate with the severity of clinical symptoms. However, ...
Humans Multiple Sclerosis White Matter Deep Learning Contrast Media Magnetic Resonance Imaging
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Reduction of respiratory motion artifacts in gadoxetate-enhanced MR with a deep learning-based filter using convolutional neural network.

European radiology Jun 17, 2020
OBJECTIVES: To reveal the utility of motion artifact reduction with convolutional neural network (MARC) in gadoxetate disodium-enhanced multi-arterial phase MRI of the liver.
Middle Aged Deep Learning Liver Neoplasms Artifacts Breath Holding Contrast Media Magnetic Resonance Imaging Aged, 80 and over Adult Male Retrospective Studies Female Aged Gadolinium DTPA Humans Neural Networks, Computer
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