AIMC Topic: Magnetic Resonance Imaging

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Prospective Comparison of Standard and Deep Learning-reconstructed Turbo Spin-Echo MRI of the Shoulder.

Radiology
Background Deep learning (DL)-based MRI reconstructions can reduce imaging times for turbo spin-echo (TSE) examinations. However, studies that prospectively use DL-based reconstructions of rapidly acquired, undersampled MRI in the shoulder are lackin...

Present and Future Innovations in AI and Cardiac MRI.

Radiology
Cardiac MRI is used to diagnose and treat patients with a multitude of cardiovascular diseases. Despite the growth of clinical cardiac MRI, complicated image prescriptions and long acquisition protocols limit the specialty and restrain its impact on ...

A Deep Learning Pipeline for Assessing Ventricular Volumes from a Cardiac MRI Registry of Patients with Single Ventricle Physiology.

Radiology. Artificial intelligence
Purpose To develop an end-to-end deep learning (DL) pipeline for automated ventricular segmentation of cardiac MRI data from a multicenter registry of patients with Fontan circulation (Fontan Outcomes Registry Using CMR Examinations [FORCE]). Materia...

Deep Learning-based Identification of Brain MRI Sequences Using a Model Trained on Large Multicentric Study Cohorts.

Radiology. Artificial intelligence
Purpose To develop a fully automated device- and sequence-independent convolutional neural network (CNN) for reliable and high-throughput labeling of heterogeneous, unstructured MRI data. Materials and Methods Retrospective, multicentric brain MRI da...

The Future of MR-Guided Radiation Therapy.

Seminars in radiation oncology
Magnetic resonance image guided radiation therapy (MRIgRT) is a relatively new technology that has already shown outcomes benefits but that has not yet reached its clinical potential. The improved soft-tissue contrast provided with MR, coupled with t...

An Early Detection and Classification of Alzheimer's Disease Framework Based on ResNet-50.

Current medical imaging
OBJECTIVE: The objective of this study is to develop a more effective early detection system for Alzheimer's disease (AD) using a Deep Residual Network (ResNet) model by addressing the issue of convolutional layers in conventional Convolutional Neura...

Retraction to: “Performance Analysis of Alexnet for Classification of Knee Osteoarthritis.

Current medical imaging
UNLABELLED: It has come to the publisher’s attention that the article is a duplication of a published paper in another journal, NeuroQuantology, available at the following link: https://neuroquantology.com/media/article_pdfs/1686-1692.pdf This raises...

Deep Learning-reconstructed Parallel Accelerated Imaging for Knee MRI.

Current medical imaging
BACKGROUND: Deep learning (DL) can improve image quality by removing noise from accelerated MRI.

Classification of Brain Tumours in MRI Images using a Convolutional Neural Network.

Current medical imaging
INTRODUCTION: Recent advances in deep learning have aided the well-being business in Medical Imaging of numerous disorders like brain tumours, a serious malignancy caused by unregulated and aberrant cell portioning. The most frequent and widely used ...