AIMC Topic: Magnetic Resonance Imaging

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Global deep learning optimization of chemical exchange saturation transfer magnetic resonance fingerprinting acquisition schedule.

NMR in biomedicine
Chemical exchange saturation transfer (CEST) MRI is a promising molecular imaging technique but suffers from long scan times and complicated processing. CEST was recently combined with magnetic resonance fingerprinting (MRF) to address these shortcom...

Stereotactic robot-assisted MRI-guided laser interstitial thermal therapy thalamotomy for medically intractable Parkinson's disease tremor: technical note and preliminary effects on 2 cases.

Acta neurochirurgica
BACKGROUND: Medically intractable Parkinson's disease (PD) tremor is a common difficult clinical situation with major impact on patient's quality of life (QOL). Deep brain stimulation (DBS) is an effective therapy but is not an option for many patien...

Associating Peritoneal Metastasis With T2-Weighted MRI Images in Epithelial Ovarian Cancer Using Deep Learning and Radiomics: A Multicenter Study.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: The preoperative diagnosis of peritoneal metastasis (PM) in epithelial ovarian cancer (EOC) is challenging and can impact clinical decision-making.

On the Early and Affordable Diagnosis of Joint Pathologies Using Acoustic Emissions, Deep Learning Decompositions and Prediction Machines.

Sensors (Basel, Switzerland)
The condition of a joint in a human being is prone to wear and several pathologies, particularly in the elderly and athletes. Current means towards assessing the overall condition of a joint to assess for a pathology involve using tools such as X-ray...

Deep learning segmentation results in precise delineation of the putamen in multiple system atrophy.

European radiology
OBJECTIVES: The precise segmentation of atrophic structures remains challenging in neurodegenerative diseases. We determined the performance of a Deep Neural Patchwork (DNP) in comparison to established segmentation algorithms regarding the ability t...

Distortion-corrected image reconstruction with deep learning on an MRI-Linac.

Magnetic resonance in medicine
PURPOSE: MRI is increasingly utilized for image-guided radiotherapy due to its outstanding soft-tissue contrast and lack of ionizing radiation. However, geometric distortions caused by gradient nonlinearities (GNLs) limit anatomical accuracy, potenti...

Rapid 3D T mapping using deep learning-assisted Look-Locker inversion recovery MRI.

Magnetic resonance in medicine
PURPOSE: Conventional 3D Look-Locker inversion recovery (LLIR) T mapping requires multi-repetition data acquisition to reconstruct images at different inversion times for T fitting. To ensure B robustness, sufficient time of delay (TD) is needed betw...

Wide and deep learning based approaches for classification of Alzheimer's disease using genome-wide association studies.

PloS one
The increasing incidence of Alzheimer's disease (AD) has been leading towards a significant growth in socioeconomic challenges. A reliable prediction of AD might be useful to mitigate or at-least slow down its progression for which, identification of...

Deep learning techniques in liver tumour diagnosis using CT and MR imaging - A systematic review.

Artificial intelligence in medicine
Deep learning has become a thriving force in the computer aided diagnosis of liver cancer, as it solves extremely complicated challenges with high accuracy over time and facilitates medical experts in their diagnostic and treatment procedures. This p...

Prediction of total knee replacement using deep learning analysis of knee MRI.

Scientific reports
Current methods for assessing knee osteoarthritis (OA) do not provide comprehensive information to make robust and accurate outcome predictions. Deep learning (DL) risk assessment models were developed to predict the progression of knee OA to total k...