A5020951225- Brain Tumor Detection and Classification
- Dementia and Cognitive Impairment Research
- Functional Brain Connectivity Studies
- Medical Image Segmentation Techniques
- Advanced Neuroimaging Techniques and Applications
- Advanced Neural Network Applications
- Machine Learning in Healthcare
- Attention Deficit Hyperactivity Disorder
- Autism Spectrum Disorder Research
- Neurological Disease Mechanisms and Treatments
- AI in cancer detection
- Advanced MRI Techniques and Applications
- CCD and CMOS Imaging Sensors
- Biometric Identification and Security
- Machine Learning in Materials Science
- Optical Imaging and Spectroscopy Techniques
- Medical Imaging and Analysis
Sichuan University
2020-2023
Chengdu University of Information Technology
2023
Nanyang Technological University
2023
Structural MRI and PET imaging play an important role in the diagnosis of Alzheimer's disease (AD), showing morphological changes glucose metabolism brain respectively. The manifestations image some cognitive impairment patients are relatively inconspicuous, for example, it still has difficulties achieving accurate through sMRI clinical practice. With emergence deep learning, convolutional neural network (CNN) become a valuable method AD-aided diagnosis, but CNN methods cannot effectively...
Alzheimer’s disease (AD) is a degenerative brain and the most common cause of dementia. In recent years, with widespread application artificial intelligence in medical field, various deep learning-based methods have been applied for AD detection using sMRI images. Many these networks achieved vs HC (Healthy Control) classification accuracy up to 90%but large number computational parameters floating point operations (FLOPs). this paper, we adopt novel ghost module, which uses series cheap...
Structural MRI and PET imaging play an important role in the diagnosis of Alzheimer's disease (AD), showing morphological changes glucose metabolism brain respectively. The manifestations image some cognitive impairment patients are relatively inconspicuous, for example, it still has difficulties achieving accurate through sMRI clinical practice. With emergence deep learning, convolutional neural network (CNN) become a valuable method AD-aided diagnosis, but CNN methods cannot effectively...
With the abundance of medical data, computer-aided AD diagnosis using multi-source and multi-modal data is a hotspot trend in research, which brings more possibilities for realization accurate assessment cognitive impairment diseases. Currently, based on convolutional neural network (CNN) still main method. But clinically, part exists non-imaging form, makes CNNs have lot challenges fusing imaging non-imaging. Graph (GNN), extends classical CNN to non-Euclidean space by graph topology,...