AIMC Topic: Magnetic Resonance Imaging
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Artificial intelligence and MRI in sinonasal tumors discrimination: where do we stand?
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
Dec 24, 2024
BACKGROUND: Artificial intelligence (AI) demonstrates high potential when applied to radiomic analysis of magnetic resonance imaging (MRI) to discriminate sinonasal tumors. This can enhance diagnostic suspicion beyond visual assessment alone and prio...
Ensemble learning-based radiomics model for discriminating brain metastasis from glioblastoma.
European journal of radiology
Dec 24, 2024
OBJECTIVE: Differentiating between brain metastasis (BM) and glioblastoma (GBM) preoperatively is challenging due to their similar imaging features on conventional brain MRI. This study aimed to enhance diagnostic accuracy through a machine learning ...
Performance of recurrent neural networks with Monte Carlo dropout for predicting pharmacokinetic parameters from dynamic contrast-enhanced magnetic resonance imaging data.
Journal of applied clinical medical physics
Dec 23, 2024
PURPOSE: To quantitatively evaluate the performance of two types of recurrent neural networks (RNNs), long short-term memory (LSTM) and gated recurrent units (GRU), using Monte Carlo dropout (MCD) to predict pharmacokinetic (PK) parameters from dynam...
MCBERT: A multi-modal framework for the diagnosis of autism spectrum disorder.
Biological psychology
Dec 23, 2024
Within the domain of neurodevelopmental disorders, autism spectrum disorder (ASD) emerges as a distinctive neurological condition characterized by multifaceted challenges. The delayed identification of ASD poses a considerable hurdle in effectively m...
Assessment of MGMT promoter methylation status in glioblastoma using deep learning features from multi-sequence MRI of intratumoral and peritumoral regions.
Cancer imaging : the official publication of the International Cancer Imaging Society
Dec 23, 2024
OBJECTIVE: This study aims to evaluate the effectiveness of deep learning features derived from multi-sequence magnetic resonance imaging (MRI) in determining the O-methylguanine-DNA methyltransferase (MGMT) promoter methylation status among glioblas...
Multi-branch CNNFormer: a novel framework for predicting prostate cancer response to hormonal therapy.
Biomedical engineering online
Dec 23, 2024
PURPOSE: This study aims to accurately predict the effects of hormonal therapy on prostate cancer (PC) lesions by integrating multi-modality magnetic resonance imaging (MRI) and the clinical marker prostate-specific antigen (PSA). It addresses the li...
Machine Learning Driven by Magnetic Resonance Imaging for the Classification of Alzheimer Disease Progression: Systematic Review and Meta-Analysis.
JMIR aging
Dec 23, 2024
BACKGROUND: To diagnose Alzheimer disease (AD), individuals are classified according to the severity of their cognitive impairment. There are currently no specific causes or conditions for this disease.
SMDFnet: Saliency multiscale dense fusion network for MRI and CT image fusion.
Computers in biology and medicine
Dec 21, 2024
MRI-CT image fusion technology combines magnetic resonance imaging (MRI) and computed tomography (CT) imaging to provide more comprehensive and accurate image information. This fusion technology can play an important role in medical diagnosis and sur...
Fusion of brain imaging genetic data for alzheimer's disease diagnosis and causal factors identification using multi-stream attention mechanisms and graph convolutional networks.
Neural networks : the official journal of the International Neural Network Society
Dec 20, 2024
Correctly diagnosing Alzheimer's disease (AD) and identifying pathogenic brain regions and genes play a vital role in understanding the AD and developing effective prevention and treatment strategies. Recent works combine imaging and genetic data, an...
Combination of deep learning reconstruction and quantification for dynamic contrast-enhanced (DCE) MRI.
Magnetic resonance imaging
Dec 20, 2024
Dynamic contrast-enhanced (DCE) MRI is an important imaging tool for evaluating tumor vascularity that can lead to improved characterization of tumor extent and heterogeneity, and for early assessment of treatment response. However, clinical adoption...
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