AIMC Topic: Brain Neoplasms
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T1-weighted MRI-based brain tumor classification using hybrid deep learning models.
Scientific reports
Feb 27, 2025
Health is fundamental to human well-being, with brain health particularly critical for cognitive functions. Magnetic resonance imaging (MRI) serves as a cornerstone in diagnosing brain health issues, providing essential data for healthcare decisions....
Enhanced glioma tumor detection and segmentation using modified deep learning with edge fusion and frequency features.
Scientific reports
Feb 26, 2025
Computer-aided automatic brain tumor detection is crucial for timely diagnosis and treatment, especially in regions with limited access to medical expertise. However, existing methods often overlook edge pixel information during tumor segmentation, l...
Performance of Machine Learning Models in Predicting BRAF Alterations Using Imaging Data in Low-Grade Glioma: A Systematic Review and Meta-Analysis.
World neurosurgery
Feb 25, 2025
BACKGROUND: Understanding the BRAF alterations preoperatively could remarkably assist in predicting tumor behavior, which leads to a more precise prognostication and management strategy. Recent advances in artificial intelligence (AI) have resulted i...
Deep learning-based Intraoperative MRI reconstruction.
European radiology experimental
Feb 25, 2025
BACKGROUND: We retrospectively evaluated the quality of deep learning (DL) reconstructions of on-scanner accelerated intraoperative MRI (iMRI) during respective brain tumor surgery.
Predictive modeling with linear machine learning can estimate glioblastoma survival in months based solely on MGMT-methylation status, age and sex.
Acta neurochirurgica
Feb 24, 2025
PURPOSE: Machine Learning (ML) has become an essential tool for analyzing biomedical data, facilitating the prediction of treatment outcomes and patient survival. However, the effectiveness of ML models heavily relies on both the choice of algorithms...
A knowledge-based planning model to identify fraction-reduction opportunities in brain stereotactic radiotherapy.
Journal of applied clinical medical physics
Feb 21, 2025
OBJECTIVE: To develop and validate a HyperArc-based RapidPlan (HARP) model for three-fraction brain stereotactic radiotherapy (SRT) plans to then use to replan previously treated five-fraction SRT plans. Demonstrating the possibility of reducing the ...
Explainable artificial intelligence of DNA methylation-based brain tumor diagnostics.
Nature communications
Feb 20, 2025
We have recently developed a machine learning classifier that enables fast, accurate, and affordable classification of brain tumors based on genome-wide DNA methylation profiles that is widely employed in the clinic. Neuro-oncology research would ben...
A novel generative model for brain tumor detection using magnetic resonance imaging.
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Feb 19, 2025
Brain tumors are a disease that kills thousands of people worldwide each year. Early identification through diagnosis is essential for monitoring and treating patients. The proposed study brings a new method through intelligent computational cells th...
Ensemble fuzzy deep learning for brain tumor detection.
Scientific reports
Feb 19, 2025
This research presents a novel ensemble fuzzy deep learning approach for brain Magnetic Resonance Imaging (MRI) analysis, aiming to improve the segmentation of brain tissues and abnormalities. The method integrates multiple components, including dive...
Comparative analysis for accurate multi-classification of brain tumor based on significant deep learning models.
Computers in biology and medicine
Feb 18, 2025
Brain tumours are a significant health concern, often resulting in severe cognitive and physiological impairments. Accurate detection and classification of brain tumours, including glioma, meningioma, and pituitary tumours, are crucial for effective ...
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