AIMC Topic: Brain Diseases
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Deep Learning Accelerated Brain Diffusion-Weighted MRI with Super Resolution Processing.
Academic radiology
Mar 22, 2024
OBJECTIVES: To investigate the clinical feasibility and image quality of accelerated brain diffusion-weighted imaging (DWI) with deep learning image reconstruction and super resolution.
A deep learning method for autism spectrum disorder identification based on interactions of hierarchical brain networks.
Behavioural brain research
Jul 27, 2023
BACKGROUND: It has been recently shown that deep learning models exhibited remarkable performance of representing functional Magnetic Resonance Imaging (fMRI) data for the understanding of brain functional activities. With hierarchical structure, dee...
Unsupervised abnormality detection in neonatal MRI brain scans using deep learning.
Scientific reports
Jul 17, 2023
Analysis of 3D medical imaging data has been a large topic of focus in the area of Machine Learning/Artificial Intelligence, though little work has been done in algorithmic (particularly unsupervised) analysis of neonatal brain MRI's. A myriad of con...
Deep-Stacked Convolutional Neural Networks for Brain Abnormality Classification Based on MRI Images.
Journal of digital imaging
May 5, 2023
An automated diagnosis system is crucial for helping radiologists identify brain abnormalities efficiently. The convolutional neural network (CNN) algorithm of deep learning has the advantage of automated feature extraction beneficial for an automate...
HGM-cNet: Integrating hippocampal gray matter probability map into a cascaded deep learning framework improves hippocampus segmentation.
European journal of radiology
Mar 15, 2023
A robust cascaded deep learning framework with integrated hippocampal gray matter (HGM) probability map was developed to improve the hippocampus segmentation (called HGM-cNet) due to its significance in various neuropsychiatric disorders such as Alzh...
Early Diagnosis of Brain Diseases Using Artificial Intelligence and EV Molecular Data: A Proposed Noninvasive Repeated Diagnosis Approach.
Cells
Dec 26, 2022
Brain-derived extracellular vesicles (BDEVs) are released from the central nervous system. Brain-related research and diagnostic techniques involving BDEVs have rapidly emerged as a means of diagnosing brain disorders because they are minimally invas...
Artificial intelligence techniques for neuropathological diagnostics and research.
Neuropathology : official journal of the Japanese Society of Neuropathology
Nov 28, 2022
Artificial intelligence (AI) research began in theoretical neurophysiology, and the resulting classical paper on the McCulloch-Pitts mathematical neuron was written in a psychiatry department almost 80 years ago. However, the application of AI in dig...
The clinical feasibility of artificial intelligence-assisted compressed sensing single-shot fluid-attenuated inversion recovery (ACS-SS-FLAIR) for evaluation of uncooperative patients with brain diseases: comparison with the conventional T2-FLAIR with parallel imaging.
Acta radiologica (Stockholm, Sweden : 1987)
Nov 24, 2022
BACKGROUND: Satisfactory magnetic resonance imaging (MRI) of those patients with involuntary head motion due to brain diseases is essential in avoiding missed diagnosis and guiding treatment.
SD-CNN: A static-dynamic convolutional neural network for functional brain networks.
Medical image analysis
Nov 12, 2022
Static functional connections (sFCs) and dynamic functional connections (dFCs) have been widely used in the resting-state functional MRI (rs-fMRI) analysis. sFCs, calculated based on entire rs-fMRI scans, can accurately describe the static topology o...
Multi-Level Functional Connectivity Fusion Classification Framework for Brain Disease Diagnosis.
IEEE journal of biomedical and health informatics
Jun 3, 2022
Brain disease diagnosis is a new hotspot in the cross research of artificial intelligence and neuroscience. Quantitative analysis of functional magnetic resonance imaging (fMRI) data can provide valuable biomarkers that contributes to clinical diagno...
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