First Clinical Investigation of Near-Infrared Window IIA/IIB Fluorescence Imaging for Precise Surgical Resection of Gliomas

First Clinical Investigation of Near-Infrared Window IIA/IIB Fluorescence Imaging for Precise Surgical Resection of Gliomas

“IEEE Transactions on Biomedical Engineering” August 2022, Vol. 69, No. 8, First Clinical Study: Application of Near-Infrared Window IIA/IIB Fluorescence Imaging in Precise Glioma Resection Surgery Cao Caiguang, Jin Zeping, Shi Xiaojing, Zhang Zhe, Xiao Anqi, Yang Junying, Ji Nan, Tian Jie (IEEE Member), Hu Zhenhua (IEEE Senior Member) Introduction...

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

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

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

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

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...