Neuroimaging has been widely used because it enables in vivo access to the structure or the function of the brain, and this access makes it become a reality for biomedical devices that monitor parameters of brain activities. The processing of neuroimaging data requires different computational algorithms to generate parameters from acquired data, thus the advances in computational techniques such as artificial intelligence, deep learning, and big data intensely contribute to neuroimaging techniques, processing tools, and their applications on biomedical devices.
This Research Topic focuses on neuroimaging, analysis techniques, and biomedical devices, including the field of pattern recognition, signal processing, image processing, machine vision, machine learning, modeling, data mining, graph theory, diffusion model, wearable equipment, etc.
We welcome submissions of Original Research and Review articles, along with Report, Data Report, Hypothesis & Theory, Methods, Mini Review, and Study Protocol, but are not limited to:
- Neuroimaging data analysis (segmentation, classification, prediction, etc.) from classical methods to the deep learning approach
- Improvements and enhancements to neuroimaging processing tools
- Computer-aided detection/diagnosis
- Applications of neuroimaging on biomedical devices (Activity recognition and wearable sensors)
Neuroimaging has been widely used because it enables in vivo access to the structure or the function of the brain, and this access makes it become a reality for biomedical devices that monitor parameters of brain activities. The processing of neuroimaging data requires different computational algorithms to generate parameters from acquired data, thus the advances in computational techniques such as artificial intelligence, deep learning, and big data intensely contribute to neuroimaging techniques, processing tools, and their applications on biomedical devices.
This Research Topic focuses on neuroimaging, analysis techniques, and biomedical devices, including the field of pattern recognition, signal processing, image processing, machine vision, machine learning, modeling, data mining, graph theory, diffusion model, wearable equipment, etc.
We welcome submissions of Original Research and Review articles, along with Report, Data Report, Hypothesis & Theory, Methods, Mini Review, and Study Protocol, but are not limited to:
- Neuroimaging data analysis (segmentation, classification, prediction, etc.) from classical methods to the deep learning approach
- Improvements and enhancements to neuroimaging processing tools
- Computer-aided detection/diagnosis
- Applications of neuroimaging on biomedical devices (Activity recognition and wearable sensors)
