AIMC Topic: Magnetic Resonance Imaging

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A deep learning MRI-based signature may provide risk-stratification strategies for nasopharyngeal carcinoma.

European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery
OBJECTIVE: As the prognosis of nasopharyngeal carcinoma (NPC) is influenced by various factors, making it difficult for clinical physicians to predict the outcome, the objective of this study was to develop a deep learning-based signature for risk st...

What benefit can be obtained from magnetic resonance imaging diagnosis with artificial intelligence in prostate cancer compared with clinical assessments?

Military Medical Research
The present study aimed to explore the potential of artificial intelligence (AI) methodology based on magnetic resonance (MR) images to aid in the management of prostate cancer (PCa). To this end, we reviewed and summarized the studies comparing the ...

MR-zero meets RARE MRI: Joint optimization of refocusing flip angles and neural networks to minimize T -induced blurring in spin echo sequences.

Magnetic resonance in medicine
PURPOSE: An end-to-end differentiable 2D Bloch simulation is used to reduce T induced blurring in single-shot turbo spin echo sequences, also called rapid imaging with refocused echoes (RARE) sequences, by using a joint optimization of refocusing fli...

A predictive signal model for dynamic cardiac magnetic resonance imaging.

Scientific reports
Robust dynamic cardiac magnetic resonance imaging (MRI) has been a long-standing endeavor-as real-time imaging can provide information on the temporal signatures of disease we currently cannot assess-with the past decade seeing remarkable advances in...

A unified hybrid transformer for joint MRI sequences super-resolution and missing data imputation.

Physics in medicine and biology
High-resolution multi-modal magnetic resonance imaging (MRI) is crucial in clinical practice for accurate diagnosis and treatment. However, challenges such as budget constraints, potential contrast agent deposition, and image corruption often limit t...

Deep learning-based affine medical image registration for multimodal minimal-invasive image-guided interventions - A comparative study on generalizability.

Zeitschrift fur medizinische Physik
Multimodal image registration is applied in medical image analysis as it allows the integration of complementary data from multiple imaging modalities. In recent years, various neural network-based approaches for medical image registration have been ...

Increased functional connectivity coupling with supplementary motor area in blepharospasm at rest.

Brain research
OBJECTIVE: To explore the abnormalities of brain function in blepharospasm (BSP) and to illustrate its neural mechanisms by assuming supplementary motor area (SMA) as the entry point.

Deep learning-assisted model-based off-resonance correction for non-Cartesian SWI.

Magnetic resonance in medicine
PURPOSE: Patient-induced inhomogeneities in the static magnetic field cause distortions and blurring (off-resonance artifacts) during acquisitions with long readouts such as in SWI. Conventional versatile correction methods based on extended Fourier ...

Fetal magnetic resonance imaging artifacts: role of deep learning to improve imaging.

Ultrasound in obstetrics & gynecology : the official journal of the International Society of Ultrasound in Obstetrics and Gynecology

Fully automated segmentation and radiomics feature extraction of hypopharyngeal cancer on MRI using deep learning.

European radiology
OBJECTIVES: To use convolutional neural network for fully automated segmentation and radiomics features extraction of hypopharyngeal cancer (HPC) tumor in MRI.