It is still a challenging task to perform the semantic segmentation with high accuracy due to
the complexity of real picture scenes. Many semantic segmentation methods based on …

Before the onset of motor symptoms, Parkinson's disease (PD) involves dysfunction of the
anterior olfactory nucleus and olfactory bulb, causing olfactory disturbance, commonly …

Group-independent component analysis (GICA) is a well-established blind source
separation technique that has been widely applied to study multi-subject functional magnetic …

The functional connectome derived from BOLD resting-state functional magnetic resonance
imaging data represents meaningful functional organizations and a shift between distinct …

Introduction Central anosmia is a potential marker of the prodrome and progression of
Parkinson's disease (PD). Resting-state functional magnetic resonance imaging studies …

Effective mental sub-health early warning mechanism is of great significance in the
protection of individual mental health. The traditional mental health assessment method is …

Many studies reported that spontaneous fluctuation of the blood oxygen level-dependent
signal exists in multiple frequency components and changes over time. By assuming a …

Independent component analysis aiming at detecting the functional connectivity among
discrete cortical brain regions has been extensively used to explore the functional magnetic …

The one-class support vector machine (OC-SVM) is a data-driven machine learning method
that has been applied as a novel technique for brain activation detection. Several …

Introduction Studies have revealed that the language network of Broca's area and
Wernicke's area is modulated by factors such as disease, gender, aging, and handedness …