AIMC Topic: Magnetic Resonance Imaging

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Artificial intelligence-based automatic assessment of lower limb torsion on MRI.

Scientific reports
Abnormal torsion of the lower limbs may adversely affect joint health. This study developed and validated a deep learning-based method for automatic measurement of femoral and tibial torsion on MRI. Axial T2-weighted sequences acquired of the hips, k...

Deep Learning Image Processing Enables 40% Faster Spinal MR Scans Which Match or Exceed Quality of Standard of Care : A Prospective Multicenter Multireader Study.

Clinical neuroradiology
OBJECTIVE: This prospective multicenter multireader study evaluated the performance of 40% scan-time reduced spinal magnetic resonance imaging (MRI) reconstructed with deep learning (DL).

Deep Learning Automated Background Phase Error Correction for Abdominopelvic 4D Flow MRI.

Radiology
Background Four-dimensional (4D) flow MRI has the potential to provide hemodynamic insights for a variety of abdominopelvic vascular diseases, but its clinical utility is currently impaired by background phase error, which can be challenging to corre...

A dynamic graph convolutional neural network framework reveals new insights into connectome dysfunctions in ADHD.

NeuroImage
The pathological mechanism of attention deficit hyperactivity disorder (ADHD) is incompletely specified, which leads to difficulty in precise diagnosis. Functional magnetic resonance imaging (fMRI) has emerged as a common neuroimaging technique for s...

Deep learning-based quantification of temporalis muscle has prognostic value in patients with glioblastoma.

British journal of cancer
BACKGROUND: Glioblastoma is the commonest malignant brain tumour. Sarcopenia is associated with worse cancer survival, but manually quantifying muscle on imaging is time-consuming. We present a deep learning-based system for quantification of tempora...

Intentional deep overfit learning (IDOL): A novel deep learning strategy for adaptive radiation therapy.

Medical physics
PURPOSE: Applications of deep learning (DL) are essential to realizing an effective adaptive radiotherapy (ART) workflow. Despite the promise demonstrated by DL approaches in several critical ART tasks, there remain unsolved challenges to achieve sat...

ALA-Net: Adaptive Lesion-Aware Attention Network for 3D Colorectal Tumor Segmentation.

IEEE transactions on medical imaging
Accurate and reliable segmentation of colorectal tumors and surrounding colorectal tissues on 3D magnetic resonance images has critical importance in preoperative prediction, staging, and radiotherapy. Previous works simply combine multilevel feature...

Estimating Effective Connectivity by Recurrent Generative Adversarial Networks.

IEEE transactions on medical imaging
Estimating effective connectivity from functional magnetic resonance imaging (fMRI) time series data has become a very hot topic in neuroinformatics and brain informatics. However, it is hard for the current methods to accurately estimate the effecti...

Automatic Searching and Pruning of Deep Neural Networks for Medical Imaging Diagnostic.

IEEE transactions on neural networks and learning systems
The field of medical imaging diagnostic makes use of a modality of imaging tests, e.g., X-rays, ultrasounds, computed tomographies, and magnetic resonance imaging, to assist physicians with the diagnostic of patients' illnesses. Due to their state-of...