Deep Learning to Quantify the Pace of Brain Aging in Relation to Neurocognitive Changes

As the global aging problem intensifies, the incidence of neurodegenerative diseases (such as Alzheimer’s Disease, AD) is increasing year by year. Brain aging (Brain Aging, BA) is one of the significant risk factors for neurodegenerative diseases, but it does not completely align with chronological age (Chronological Age, CA). Traditional methods f...

Enhancing Passive Cavitation Imaging Using Pth Root Compression Delay, Sum, and Integrate Beamforming: In Vitro and In Vivo Studies

Application of pth Root Compression Delay, Sum and Integrate Beamforming in Passive Cavitation Imaging Academic Background Passive Cavitation Imaging (PCI) is a technique used to monitor bubble activity during ultrasound therapy, widely applied in treatment scenarios such as drug delivery and tissue ablation (e.g., Histotripsy). However, existing P...

Analysis of Pelvis and Lower Limb Coordination in Stroke Patients Using Smartphone-Based Motion Capture

Analysis of Pelvis and Lower Limb Coordination in Stroke Patients Using Smartphone-Based Motion Capture Technology Academic Background Stroke is one of the diseases with the highest incidence, disability, and mortality rates worldwide, with up to 15 million new cases each year. Among them, 20%-30% of stroke patients develop hemiplegic gait, which i...

Passive Beamforming Metasurfaces for Microwave-Induced Thermoacoustic Imaging

Passive Beamforming Metasurfaces for Microwave-Induced Thermoacoustic Imaging Academic Background Microwave-induced thermoacoustic imaging (MTAI) is an emerging medical imaging technology that combines the advantages of microwave and ultrasound imaging. It generates ultrasonic waves (i.e., thermoacoustic signals) by irradiating biological tissues w...

Two-source Validation of Online Surface EMG Decomposition Using Progressive FastICA Peel-off

Two-Source Validation Study of Online Surface Electromyogram Decomposition Academic Background Surface electromyogram (SEMG) signals are crucial representations of muscle activity and are widely used in fields such as sports rehabilitation, robotic control, and human-machine interaction. However, SEMG signals are challenging to decompose due to the...

Imitation Learning for Path Planning in Cardiac Percutaneous Interventions

Application of Imitation Learning in Path Planning for Percutaneous Cardiac Interventions Academic Background Cardiac valve diseases, particularly mitral regurgitation (MR), are the third most common type of valvular heart disease globally and have a higher incidence in the elderly population. MR is characterized by the incomplete closure of the mi...