A Wearable Fluorescence Imaging Device for Intraoperative Identification of Human Brain Tumors

Engineering, Electrical Engineering, Medicine, Neurology, Neurosurgery, Medical Imaging, Life Sciences, Bioengineering,
Intraoperative imaging device   Malignant glioma   Brain tumors   Fluorescence-guided surgery   Wearable device  

Malignant Glioma (MG) Report Malignant Glioma (MG) is the most common type of primary malignant brain tumor. Surgical resection of MG remains the cornerstone of treatment, and the extent of resection is highly correlated with patient survival. However, it is difficult to distinguish tumor tissue from normal tissue during surgery, which greatly limi...

Normalizing Flow-Based Distribution Estimation of Pharmacokinetic Parameters in Dynamic Contrast-Enhanced Magnetic Resonance Imaging

Engineering, Electrical Engineering, Information Science, Artificial Intelligence, Medicine, Medical Laboratory Science, Medical Imaging, Oncology,
normalizing flow   pharmacokinetic parameters   dynamic contrast-enhanced MRI   maximum likelihood estimation   posterior distribution  

In modern medical diagnostics and clinical research, Dynamic Contrast-Enhanced Magnetic Resonance Imaging (DCE-MRI) technology provides significant information regarding tissue pathophysiology. By fitting a Tracer-Kinetic (TK) model, pharmacokinetic (PK) parameters can be extracted from time-series MRI signals. However, these estimated PK parameter...

Physics-Informed Deep Learning for Musculoskeletal Modeling: Predicting Muscle Forces and Joint Kinematics from Surface EMG

Engineering, Electrical Engineering, Information Science, Computer Science, Automation, Artificial Intelligence, Medicine, Orthopedics, Medical Laboratory Science, Medical Imaging, Life Sciences, Bioengineering,
physics-informed   deep learning   musculoskeletal modeling   EMG   muscle forces   joint kinematics  

Musculoskeletal models have been widely used in biomechanical analysis because they can estimate motion variables that are difficult to measure directly in living organisms, such as muscle forces and joint moments. Traditional physics-driven computational musculoskeletal models can explain the dynamic interactions between neural inputs to muscles, ...

Deep Learning-Based Assessment Model for Real-Time Identification of Visual Learners Using Raw EEG

Engineering, Electrical Engineering, Information Science, Computer Science, Artificial Intelligence, Medicine, Neurology, Life Sciences, Bioengineering,
deep learning   real-time identification   visual learners   EEG   machine learning   electroencephalogram   classification  

In the current educational environment, understanding students’ learning styles is crucial for improving their learning efficiency. Specifically, the identification of visual learning styles can help teachers and students adopt more effective strategies in the teaching and learning process. Currently, automatic identification of visual learning sty...

Multi-Feature Attention Convolutional Neural Network for Motor Imagery Decoding

Engineering, Electrical Engineering, Information Science, Automation, Artificial Intelligence, Medicine, Medical Laboratory Science, Neurology, Life Sciences, Bioengineering,
multi-feature attention   convolutional neural networks   motor imagery   brain-computer interface   lightweight model  

Brain-Computer Interface (BCI) is a communication method that connects the nervous system to the external environment. Motor Imagery (MI) is the cornerstone of BCI research, referring to the internal rehearsal before physical execution. Non-invasive techniques such as Electroencephalography (EEG) can record neural activities with high temporal reso...