AIMC Topic: Magnetic Resonance Imaging

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Deep Learning Approach for MRI in the Classification of Anterior Talofibular Ligament Injuries.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Diagnosing anterior talofibular ligament (ATFL) injuries differs among radiologists. Further assessment of ATFL tears is valuable for clinical decision-making.

Applying machine learning classifiers to automate quality assessment of paediatric dynamic susceptibility contrast (DSC-) MRI data.

The British journal of radiology
OBJECTIVE: Investigate the performance of qualitative review (QR) for assessing dynamic susceptibility contrast (DSC-) MRI data quality in paediatric normal brain and develop an automated alternative to QR.

Deep learning based automatic contour refinement for inaccurate auto-segmentation in MR-guided adaptive radiotherapy.

Physics in medicine and biology
Fast and accurate auto-segmentation is essential for magnetic resonance-guided adaptive radiation therapy (MRgART). Deep learning auto-segmentation (DLAS) is not always clinically acceptable, particularly for complex abdominal organs. We previously r...

Prospective intraindividual comparison of a standard 2D TSE MRI protocol for ankle imaging and a deep learning-based 2D TSE MRI protocol with a scan time reduction of 48.

La Radiologia medica
PURPOSE: Magnetic resonance imaging (MRI) scan time remains a limited and valuable resource. This study evaluates the diagnostic performance of a deep learning (DL)-based accelerated TSE study protocol compared to a standard TSE study protocol in ank...

Evaluation of a deep learning-based reconstruction method for denoising and image enhancement of shoulder MRI in patients with shoulder pain.

European radiology
OBJECTIVES: To evaluate the diagnostic performance of an automated reconstruction algorithm combining MR imaging acquired using compressed SENSE (CS) with deep learning (DL) in order to reconstruct denoised high-quality images from undersampled MR im...

Contribution of Retzius-sparing robot-assisted radical prostatectomy to the mechanism of urinary continence as demonstrated by dynamic MRI.

Scientific reports
Retzius-sparing robot-assisted radical prostatectomy (RARP) has been reported to exhibit better postoperative urinary continence, but the reasons behind this are unknown. This study included 254 cases who underwent RARP and underwent postoperative dy...

Segmentation of the aorta in systolic phase from 4D flow MRI: multi-atlas vs. deep learning.

Magma (New York, N.Y.)
OBJECTIVE: In the management of the aortic aneurysm, 4D flow magnetic resonance Imaging provides valuable information for the computation of new biomarkers using computational fluid dynamics (CFD). However, accurate segmentation of the aorta is requi...

Implementable Deep Learning for Multi-sequence Proton MRI Lung Segmentation: A Multi-center, Multi-vendor, and Multi-disease Study.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Recently, deep learning via convolutional neural networks (CNNs) has largely superseded conventional methods for proton ( H)-MRI lung segmentation. However, previous deep learning studies have utilized single-center data and limited acqui...

Predicting the prognosis of lower rectal cancer using preoperative magnetic resonance imaging with artificial intelligence.

Techniques in coloproctology
BACKGROUND: There are various preoperative treatments that are useful for controlling local or distant metastases in lower rectal cancer. For planning perioperative management, preoperative stratification of optimal treatment strategies for each case...

Technical note: Progressive deep learning: An accelerated training strategy for medical image segmentation.

Medical physics
BACKGROUND: Recent advancements in Deep Learning (DL) methodologies have led to state-of-the-art performance in a wide range of applications especially in object recognition, classification, and segmentation of medical images. However, training moder...