AIMC Topic:
Magnetic Resonance Imaging

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Deep Learning Based on ResNet-18 for Classification of Prostate Imaging-Reporting and Data System Category 3 Lesions.

Academic radiology Feb 1, 2024
RATIONALE AND OBJECTIVES: To explore the classification and prediction efficacy of the deep learning model for benign prostate lesions, non-clinically significant prostate cancer (non-csPCa) and clinically significant prostate cancer (csPCa) in Prost...
Image Interpretation, Computer-Assisted Prostatic Neoplasms Prostate Retrospective Studies Aged Male Middle Aged Deep Learning Magnetic Resonance Imaging Humans
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Compressed sensing with deep learning reconstruction: Improving capability of gadolinium-EOB-enhanced 3D T1WI.

Magnetic resonance imaging Feb 1, 2024
PURPOSE: The purpose of this study was to determine the utility of compressed sensing (CS) with deep learning reconstruction (DLR) for improving spatial resolution, image quality and focal liver lesion detection on high-resolution contrast-enhanced T...
Deep Learning Liver Neoplasms Carcinoma, Hepatocellular Humans Gadolinium Contrast Media Chemoembolization, Therapeutic Magnetic Resonance Imaging
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The Success of Deep Learning Modalities in Evaluating Modic Changes.

World neurosurgery Feb 1, 2024
BACKGROUND: Modic changes are pathologies that are common in the population and cause low back pain. The aim of the study is to analyze the modic changes detected in magnetic resonance imaging (MRI) using deep learning modalities.
Humans Neural Networks, Computer Magnetic Resonance Imaging Low Back Pain Lumbosacral Region Female Male Deep Learning
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Use of MRI-based deep learning radiomics to diagnose sacroiliitis related to axial spondyloarthritis.

European journal of radiology Feb 1, 2024
OBJECTIVES: This study aimed to evaluate the performance of a deep learning radiomics (DLR) model, which integrates multimodal MRI features and clinical information, in diagnosing sacroiliitis related to axial spondyloarthritis (axSpA).
Deep Learning Magnetic Resonance Imaging Sacroiliac Joint Retrospective Studies Radiomics Sacroiliitis Axial Spondyloarthritis Humans
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Point-Of-Care low-field MRI in acute Stroke (POCS): protocol for a multicentric prospective open-label study evaluating diagnostic accuracy.

BMJ open Jan 31, 2024
INTRODUCTION: Fast and accurate diagnosis of acute stroke is crucial to timely initiate reperfusion therapies. Conventional high-field (HF) MRI yields the highest accuracy in discriminating early ischaemia from haemorrhages and mimics. Rapid access t...
Artificial Intelligence Research Design Stroke Humans Prospective Studies Point-of-Care Systems Magnetic Resonance Imaging Multicenter Studies as Topic
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Systematic comparison of 3D Deep learning and classical machine learning explanations for Alzheimer's Disease detection.

Computers in biology and medicine Jan 30, 2024
Black-box deep learning (DL) models trained for the early detection of Alzheimer's Disease (AD) often lack systematic model interpretation. This work computes the activated brain regions during DL and compares those with classical Machine Learning (M...
Alzheimer Disease Humans Machine Learning Deep Learning Magnetic Resonance Imaging Australia
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Unsupervised motion artifact correction of turbo spin-echo MRI using deep image prior.

Magnetic resonance in medicine Jan 28, 2024
PURPOSE: In MRI, motion artifacts can significantly degrade image quality. Motion artifact correction methods using deep neural networks usually required extensive training on large datasets, making them time-consuming and resource-intensive. In this...
Magnetic Resonance Imaging Motion Artifacts Computer Simulation Deep Learning Image Processing, Computer-Assisted Algorithms Brain Humans Neural Networks, Computer
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Predictive uncertainty in deep learning-based MR image reconstruction using deep ensembles: Evaluation on the fastMRI data set.

Magnetic resonance in medicine Jan 28, 2024
PURPOSE: To estimate pixel-wise predictive uncertainty for deep learning-based MR image reconstruction and to examine the impact of domain shifts and architecture robustness.
Image Processing, Computer-Assisted Brain Humans Magnetic Resonance Imaging Deep Learning Algorithms Uncertainty Databases, Factual
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Using Deep Learning and B-Splines to Model Blood Vessel Lumen from 3D Images.

Sensors (Basel, Switzerland) Jan 28, 2024
Accurate geometric modeling of blood vessel lumen from 3D images is crucial for vessel quantification as part of the diagnosis, treatment, and monitoring of vascular diseases. Our method, unlike other approaches which assume a circular or elliptical ...
Neural Networks, Computer Deep Learning Algorithms Imaging, Three-Dimensional Magnetic Resonance Imaging
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Diagnosis of skull-base invasion by nasopharyngeal tumors on CT with a deep-learning approach.

Japanese journal of radiology Jan 27, 2024
PURPOSE: To develop a convolutional neural network (CNN) model to diagnose skull-base invasion by nasopharyngeal malignancies in CT images and evaluate the model's diagnostic performance.
Neoplasm Invasiveness Nasopharyngeal Neoplasms Skull Base Skull Base Neoplasms Humans Middle Aged Deep Learning Retrospective Studies Magnetic Resonance Imaging Tomography, X-Ray Computed Sensitivity and Specificity Female Male Aged Adult
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