A5101411475- Brain Tumor Detection and Classification
- AI in cancer detection
- Advanced MRI Techniques and Applications
- Functional Brain Connectivity Studies
- Medical Imaging and Analysis
- Dementia and Cognitive Impairment Research
- Optical Systems and Laser Technology
- Traditional Chinese Medicine Studies
- Advanced Surface Polishing Techniques
- Advanced Neuroimaging Techniques and Applications
- Machine Learning in Healthcare
- Artificial Intelligence in Healthcare
- Advanced Measurement and Detection Methods
- Optical measurement and interference techniques
- Advanced Manufacturing and Logistics Optimization
Wenzhou University
2021-2023
Zhejiang Lab
2023
Resting-state functional magnetic resonance imaging (rs-fMRI) has been used to construct connectivity (FC) in the brain for diagnosis and analysis of disease. Current studies typically use Pearson correlation coefficient dynamic FC (dFC) networks, then this as a network metric obtain necessary features disease analysis. This simple observational approach makes it difficult extract potential high-level from representations, also ignores rich information on spatial temporal variability FC. In...
The brain is the most sophisticated and complex organ in human body. Nowadays, diagnosing diverse diseases a hot topic. Alzheimer's Disease (AD), Autism Spectrum Disorder (ASD), others are common diseases. With increased usage of Artificial Intelligence (AI) medical image analysis, endeavor to make AI comprehend images for assisting doctors making objective diagnoses has gained considerable attention. Resting-state functional magnetic resonance imaging (rs-fMRI) widely used tool analyzing...
Abstract The early and effective diagnosis of Alzheimer's disease(AD) mild cognitive impairment(MCI) has received increasing attention in recent years, but most the existing studies do not pay enough to spatial structure information structural magnetic resonance images(MRI), go deeper explore potential connection between slices slices, thus making network models less accurate, poor generalization ability. To context this research is designed develop a new deep learning method effectively...
Abstract Background: The early and effective diagnosis of Alzheimer's disease(AD) mild cognitive impairment(MCI) has received increasing attention in recent years.There are many machine learning deep methods that widely used neural image analysis, among which structural magnetic resonance images play an important role intervention for patients with disease impairment as a data pattern, studies have constructed network models based on images, but most the existing do not pay enough to spatial...