AIMC Topic: Magnetic Resonance Imaging

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Accuracy of robot-assisted stereotactic MRI-guided laser ablation in children with epilepsy.

Journal of neurosurgery. Pediatrics
OBJECTIVE: Robot-assisted (RA) stereotactic MRI-guided laser ablation has been reported to be a safe and effective technique for the treatment of epileptogenic foci in children and adults. In this study the authors aimed to assess the accuracy of RA ...

Estimating Uncertainty in Neural Networks for Cardiac MRI Segmentation: A Benchmark Study.

IEEE transactions on bio-medical engineering
OBJECTIVE: Convolutional neural networks (CNNs) have demonstrated promise in automated cardiac magnetic resonance image segmentation. However, when using CNNs in a large real-world dataset, it is important to quantify segmentation uncertainty and ide...

Reduction in Radiologist Interpretation Time of Serial CT and MR Imaging Findings with Deep Learning Identification of Relevant Priors, Series and Finding Locations.

Academic radiology
RATIONALE AND OBJECTIVES: Finding comparison to relevant prior studies is a requisite component of the radiology workflow. The purpose of this study was to evaluate the impact of a deep learning tool simplifying this time-consuming task by automatica...

Sequence based local-global information fusion framework for vertebrae detection under pathological and FOV variation challenges.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Automated vertebrae detection (identification and localization) aims to identify vertebrae and locate their centroids in medical images, which is a critical step of spinal computer-aided systems. However, due to unpredictable field-of-view and variou...

Automated 3-dimensional MRI segmentation for the posterosuperior rotator cuff tear lesion using deep learning algorithm.

PloS one
INTRODUCTION: Rotator cuff tear (RCT) is a challenging and common musculoskeletal disease. Magnetic resonance imaging (MRI) is a commonly used diagnostic modality for RCT, but the interpretation of the results is tedious and has some reliability issu...

Diagnostic performance of deep learning-based reconstruction algorithm in 3D MR neurography.

Skeletal radiology
OBJECTIVE: The study aims to evaluate the diagnostic performance of deep learning-based reconstruction method (DLRecon) in 3D MR neurography for assessment of the brachial and lumbosacral plexus.

Deep learning HASTE sequence compared with T2-weighted BLADE sequence for liver MRI at 3 Tesla: a qualitative and quantitative prospective study.

European radiology
OBJECTIVES: To qualitatively and quantitatively compare a single breath-hold fast half-Fourier single-shot turbo spin echo sequence with deep learning reconstruction (DL HASTE) with T2-weighted BLADE sequence for liver MRI at 3 T.

US regulatory considerations for low field magnetic resonance imaging systems.

Magma (New York, N.Y.)
Although there has been a resurgence of interest in low field magnetic resonance imaging (MRI) systems in recent years, low field MRI is not a new concept. FDA has a long history of evaluating the safety and effectiveness of MRI systems encompassing ...

Self-Propelled Janus Nanocatalytic Robots Guided by Magnetic Resonance Imaging for Enhanced Tumor Penetration and Therapy.

Journal of the American Chemical Society
Biomedical micro/nanorobots as active delivery systems with the features of self-propulsion and controllable navigation have made tremendous progress in disease therapy and diagnosis, detection, and biodetoxification. However, existing micro/nanorobo...

A Deep Learning Pipeline Using Prior Knowledge for Automatic Evaluation of Placenta Accreta Spectrum Disorders With MRI.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: The diagnosis of prenatal placenta accreta spectrum (PAS) with magnetic resonance imaging (MRI) is highly dependent on radiologists' experience. A deep learning (DL) method using the prior knowledge that PAS-related signs are generally fo...