AIMC Topic: Brain

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Deep learning radiomics nomograms predict Isocitrate dehydrogenase (IDH) genotypes in brain glioma: A multicenter study.

Magnetic resonance imaging Dec 19, 2024
PURPOSE: To explore the feasibility of Deep learning radiomics nomograms (DLRN) in predicting IDH genotype.
Isocitrate Dehydrogenase Humans Brain Adult Nomograms Radiomics Retrospective Studies Middle Aged Brain Neoplasms Female Deep Learning Male Glioma Aged ROC Curve Magnetic Resonance Imaging Genotype Mutation
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Image quality assessment and white matter hyperintensity quantification in two accelerated high-resolution 3D FLAIR techniques: Wave-CAIPI and deep learning-based SPACE.

Clinical radiology Dec 19, 2024
AIM: To compare the image quality obtained using two accelerated high-resolution 3D fluid-attenuated inversion recovery (FLAIR) techniques for the brain-deep learning-reconstruction SPACE (DL-SPACE) and Wave-CAIPI FLAIR.
White Matter Male Female Humans Middle Aged Brain Aged Deep Learning Retrospective Studies Aged, 80 and over Adult Imaging, Three-Dimensional Magnetic Resonance Imaging Image Interpretation, Computer-Assisted Signal-To-Noise Ratio
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Neuropathology of focal epilepsy: the promise of artificial intelligence and digital Neuropathology 3.0.

Pathology Dec 19, 2024
Focal lesions of the human neocortex often cause drug-resistant epilepsy, yet ​surgical resection of the epileptogenic region has been proven as a successful strategy to control seizures in a carefully selected patient cohort. Continuous efforts to s...
Brain Epilepsies, Partial Neuropathology Humans Artificial Intelligence
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Generative Adversarial Network Based Contrast Enhancement: Synthetic Contrast Brain Magnetic Resonance Imaging.

Academic radiology Dec 18, 2024
RATIONALE AND OBJECTIVES: Magnetic resonance imaging (MRI) is a vital tool for diagnosing neurological disorders, frequently utilising gadolinium-based contrast agents (GBCAs) to enhance resolution and specificity. However, GBCAs present certain risk...
Image Enhancement Generative Adversarial Networks Female Aged Humans Young Adult Male Neural Networks, Computer Middle Aged Adult Brain Contrast Media Magnetic Resonance Imaging
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Noise Reduction in Brain CT: A Comparative Study of Deep Learning and Hybrid Iterative Reconstruction Using Multiple Parameters.

Tomography (Ann Arbor, Mich.) Dec 18, 2024
OBJECTIVES: We evaluated the noise reduction effects of deep learning reconstruction (DLR) and hybrid iterative reconstruction (HIR) in brain computed tomography (CT).
Phantoms, Imaging Humans Image Processing, Computer-Assisted Radiographic Image Interpretation, Computer-Assisted Adult Signal-To-Noise Ratio Male Middle Aged Deep Learning Brain Tomography, X-Ray Computed Female Aged
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MHAGuideNet: a 3D pre-trained guidance model for Alzheimer's Disease diagnosis using 2D multi-planar sMRI images.

BMC medical imaging Dec 18, 2024
BACKGROUND: Alzheimer's Disease is a neurodegenerative condition leading to irreversible and progressive brain damage, with possible features such as structural atrophy. Effective precision diagnosis is crucial for slowing disease progression and red...
Sensitivity and Specificity Male Imaging, Three-Dimensional Magnetic Resonance Imaging Female Aged Aged, 80 and over Alzheimer Disease Image Interpretation, Computer-Assisted Atrophy Humans Neural Networks, Computer Brain
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Leveraging transfer learning-driven convolutional neural network-based semantic segmentation model for medical image analysis using MRI images.

Scientific reports Dec 18, 2024
Recognition and segmentation of brain tumours (BT) using MR images are valuable and tedious processes in the healthcare industry. Earlier diagnosis and localization of BT provide timely options to select effective treatment plans for the doctors and ...
Neural Networks, Computer Machine Learning Brain Brain Neoplasms Humans Deep Learning Semantics Image Processing, Computer-Assisted Magnetic Resonance Imaging
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Incorporating Radiologist Knowledge Into MRI Quality Metrics for Machine Learning Using Rank-Based Ratings.

Journal of magnetic resonance imaging : JMRI Dec 17, 2024
BACKGROUND: Deep learning (DL) often requires an image quality metric; however, widely used metrics are not designed for medical images.
Neural Networks, Computer Machine Learning Algorithms Databases, Factual Humans Image Processing, Computer-Assisted Brain Magnetic Resonance Imaging Retrospective Studies Radiologists Reproducibility of Results Image Interpretation, Computer-Assisted Deep Learning
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Convolutional neural network-assisted Raman spectroscopy for high-precision diagnosis of glioblastoma.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy Dec 17, 2024
Glioblastoma multiforme (GBM) is the most lethal intracranial tumor with a median survival of approximately 15 months. Due to its highly invasive properties, it is particularly difficult to accurately identify the tumor margins intraoperatively. The ...
Brain Neoplasms Animals Convolutional Neural Networks Mice Spectrum Analysis, Raman Glioblastoma Humans Neural Networks, Computer Brain
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Brain networks and intelligence: A graph neural network based approach to resting state fMRI data.

Medical image analysis Dec 16, 2024
Resting-state functional magnetic resonance imaging (rsfMRI) is a powerful tool for investigating the relationship between brain function and cognitive processes as it allows for the functional organization of the brain to be captured without relying...
Magnetic Resonance Imaging Brain Mapping Intelligence Nerve Net Graph Neural Networks Brain Female Male Adolescent Humans Neural Networks, Computer
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