AIMC Topic: Magnetic Resonance Imaging

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Machine learning with multiple modalities of brain magnetic resonance imaging data to identify the presence of bipolar disorder.

Journal of affective disorders
BACKGROUND: Bipolar disorder (BD) is a chronic psychiatric mood disorder that is solely diagnosed based on clinical symptoms. These symptoms often overlap with other psychiatric disorders. Efforts to use machine learning (ML) to create predictive mod...

Deep learning constrained compressed sensing reconstruction improves high-resolution three-dimensional (3D) T2-weighted turbo spin echo magnetic resonance imaging (MRI) of the lumbar spine.

Clinical radiology
AIM: We sought to assess the image quality of three-dimensional (3D) T2-weighted (T2w) turbo spin echo (TSE) sequences with deep learning (DL)-constrained compressed sensing (CS) reconstruction relative to a reference two-dimensional (2D) T2w TSE seq...

Prediction of fetal brain gestational age using multihead attention with Xception.

Computers in biology and medicine
Accurate gestational age (GA) prediction is crucial for monitoring fetal development and ensuring optimal prenatal care. Traditional methods often face challenges in terms of precision and prediction efficiency. In this context, leveraging modern dee...

DeepASD: a deep adversarial-regularized graph learning method for ASD diagnosis with multimodal data.

Translational psychiatry
Autism Spectrum Disorder (ASD) is a prevalent neurological condition with multiple co-occurring comorbidities that seriously affect mental health. Precisely diagnosis of ASD is crucial to intervention and rehabilitation. A single modality may not ful...

Accelerated CEST imaging through deep learning quantification from reduced frequency offsets.

Magnetic resonance in medicine
PURPOSE: To shorten CEST acquisition time by leveraging Z-spectrum undersampling combined with deep learning for CEST map construction from undersampled Z-spectra.

An hetero-modal deep learning framework for medical image synthesis applied to contrast and non-contrast MRI.

Biomedical physics & engineering express
Some pathologies such as cancer and dementia require multiple imaging modalities to fully diagnose and assess the extent of the disease. Magnetic resonance imaging offers this kind of polyvalence, but examinations take time and can require contrast a...

Automated Three-Dimensional Imaging and Pfirrmann Classification of Intervertebral Disc Using a Graphical Neural Network in Sagittal Magnetic Resonance Imaging of the Lumbar Spine.

Journal of imaging informatics in medicine
This study aimed to develop a graph neural network (GNN) for automated three-dimensional (3D) magnetic resonance imaging (MRI) visualization and Pfirrmann grading of intervertebral discs (IVDs), and benchmark it against manual classifications. Lumbar...

MRI-compatible and sensorless haptic feedback for cable-driven medical robotics to perform teleoperated needle-based interventions.

International journal of computer assisted radiology and surgery
PURPOSE: Surgical robotics have demonstrated their significance in assisting physicians during minimally invasive surgery. Especially, the integration of haptic and tactile feedback technologies can enhance the surgeon's performance and overall patie...