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Journal of neuroradiology = Journal de neuroradiologie

Showing 1 to 9 of 9 articles

Deep learning segmentation-based bone removal from computed tomography of the brain improves subdural hematoma detection.

Journal of neuroradiology = Journal de neuroradiologie Nov 8, 2024
PURPOSE: Timely identification of intracranial blood products is clinically impactful, however the detection of subdural hematoma (SDH) on non-contrast CT scans of the head (NCCTH) is challenging given interference from the adjacent calvarium. This w...
Humans Algorithms Tomography, X-Ray Computed Female Radiographic Image Interpretation, Computer-Assisted Male Skull Deep Learning Hematoma, Subdural
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Intra and inter-regional functional connectivity of the human brain due to Task-Evoked fMRI Data classification through CNN & LSTM.

Journal of neuroradiology = Journal de neuroradiologie Feb 25, 2024
BACKGROUND AND PURPOSE: Olfaction is an early marker of neurodegenerative disease. Standard olfactory function is essential due to the importance of olfaction in human life. The psychophysical evaluation assesses the olfactory function commonly. It i...
Magnetic Resonance Imaging Brain Mapping Olfaction Disorders Brain Humans Male Female Neural Networks, Computer Middle Aged Adult Algorithms Deep Learning
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Predicting brain age gap with radiomics and automl: A Promising approach for age-Related brain degeneration biomarkers.

Journal of neuroradiology = Journal de neuroradiologie Sep 16, 2023
The Brain Age Gap (BAG), which refers to the difference between chronological age and predicted neuroimaging age, is proposed as a potential biomarker for age-related brain degeneration. However, existing brain age prediction models usually rely on a...
Machine Learning Biomarkers Brain Humans Radiomics Male Aging Female Aged Aged, 80 and over Cognitive Dysfunction Alzheimer Disease Neuroimaging
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AI-based classification of three common malignant tumors in neuro-oncology: A multi-institutional comparison of machine learning and deep learning methods.

Journal of neuroradiology = Journal de neuroradiologie Aug 29, 2023
PURPOSE: To determine if machine learning (ML) or deep learning (DL) pipelines perform better in AI-based three-class classification of glioblastoma (GBM), intracranial metastatic disease (IMD) and primary CNS lymphoma (PCNSL).
Glioblastoma Multiparametric Magnetic Resonance Imaging Brain Neoplasms Male Middle Aged Deep Learning Lymphoma Magnetic Resonance Imaging Female Aged Adult Machine Learning Retrospective Studies Humans
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How feasible is end-to-end deep learning for clinical neuroimaging?

Journal of neuroradiology = Journal de neuroradiologie Oct 13, 2022
Humans Deep Learning Neural Networks, Computer Neuroimaging Brain
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Dense, deep learning-based intracranial aneurysm detection on TOF MRI using two-stage regularized U-Net.

Journal of neuroradiology = Journal de neuroradiologie Mar 17, 2022
BACKGROUND AND PURPOSE: The prevalence of unruptured intracranial aneurysms in the general population is high and aneurysms are usually asymptomatic. Their diagnosis is often fortuitous on MRI and might be difficult and time consuming for the radiolo...
Humans Retrospective Studies Sensitivity and Specificity Magnetic Resonance Angiography Deep Learning Angiography, Digital Subtraction Imaging, Three-Dimensional Intracranial Aneurysm Magnetic Resonance Imaging
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The effect of a post-scan processing denoising system on image quality and morphometric analysis.

Journal of neuroradiology = Journal de neuroradiologie Dec 2, 2021
PURPOSE: MR image quality and subsequent brain morphometric analysis are inevitably affected by noise. The purpose of this study was to evaluate the effectiveness of an artificial intelligence (AI)-based post-scan processing denoising system, intelli...
Image Processing, Computer-Assisted Magnetic Resonance Imaging Signal-To-Noise Ratio Brain Reproducibility of Results Cross-Sectional Studies Artificial Intelligence Algorithms Humans
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Artificial neuroradiology: Between human and artificial networks of neurons?

Journal of neuroradiology = Journal de neuroradiologie Jul 11, 2019
Humans Neural Networks, Computer Periodicals as Topic Neuroradiography Machine Learning Brain Diagnosis, Computer-Assisted
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Presurgical differentiation between malignant haemangiopericytoma and angiomatous meningioma by a radiomics approach based on texture analysis.

Journal of neuroradiology = Journal de neuroradiologie Jun 18, 2019
PURPOSE: To assess whether a machine-learning model based on texture analysis (TA) could yield a more accurate diagnosis in differentiating malignant haemangiopericytoma (HPC) from angiomatous meningioma (AM).
Sensitivity and Specificity Male Hemangiopericytoma Retrospective Studies Middle Aged Meningioma Humans Female Meningeal Neoplasms Machine Learning Diagnosis, Computer-Assisted Adult Neuroradiography Magnetic Resonance Imaging Preoperative Care
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