Research Background Fluorescence spectroscopy is a widely used method for identifying and quantifying fluorescent substances (fluorophores). However, quantifying the fluorophores of interest becomes challenging when the material contains other fluorophores (baseline fluorophores), especially when the emission spectrum of the baseline is not well-de...
Multi-Level Feature Exploration and Fusion Network for Prediction of IDH Status in MRI Background Glioma is the most common malignant primary brain tumor in adults. According to the 2021 World Health Organization (WHO) classification of tumors, genotype plays a significant role in the classification of tumor subtypes, especially the isocitrate dehy...
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...
Classification of 3D MRI Gliomas and Alzheimer’s Disease Based on the Siamese-Transport Domain Adaptation Framework Background In computer-aided diagnosis, 3D magnetic resonance imaging (MRI) screening plays a vital role in the early diagnosis of various brain diseases, effectively preventing the deterioration of the condition. Glioma is a common m...
DeepSleepNet: An Automatic Sleep Stage Scoring Model Based on Single-Channel EEG Background Introduction Sleep has a significant impact on human health, and monitoring sleep quality is crucial in medical research and practice. Typically, sleep experts score sleep stages by analyzing various physiological signals such as electroencephalogram (EEG), ...
In recent years, Virtual Reality (VR) technology has become increasingly common, with related hardware becoming more affordable. For example, current head-mounted displays (HMDs) on the market not only offer high-resolution displays but also feature precise head and handheld controller tracking. Initially, these technologies were mostly used in the...
Sleep stage classification is crucial for sleep quality assessment and disease diagnosis. However, existing classification methods still face numerous challenges in handling the spatial and temporal features of time-varying multi-channel brain signals, coping with individual differences in biological signals, and model interpretability. Traditional...
Background Introduction Motor Imagery (MI) refers to performing activities through imagination without actual muscle movement. This paradigm is widely used in Brain-Computer Interface (BCI) to decode brain activities into control commands for external devices. Specifically, Electroencephalography (EEG) is widely used in BCI due to its relative affo...
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, ...
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...