Dr. Pengfei Song has developed methods of real-time SR-UMI. Current SR-UMI requires hours of data post-processing, making it impractical for clinical, diagnostic...
Dr. Pengfei Song has developed methods of real-time SR-UMI. Current SR-UMI requires hours of data post-processing, making it impractical for clinical, diagnostic applications. Implementing advances in deep learning and parallel computing, Dr. Song's team was able to realize real-time microbubble signal extraction, separation, localization, tracking, and quantitative analysis and display. This technology has a wide range of clinical applications including but not limited to the diagnosis and characterization of many disorders including cancer, cardiovascular disease, and neurological diseases.
Researchers have developed a method that accelerates data acquisition for Fourier transform-ion cyclotron resonance (FT-ICR) mass spectrometry imaging (MSI) by ten folds...
Researchers have developed a method that accelerates data acquisition for Fourier transform-ion cyclotron resonance (FT-ICR) mass spectrometry imaging (MSI) by ten folds while maintaining high mass and spatial resolution and accuracy. Compared to other methods in MSI data acquisition/reconstruction, this approach exploits redundancy in the data, eventually reducing the time for data collection. The primary applications of the technology will be in clinical diagnostics, drug metabolism studies and localization/characterization of biomolecules within tissue samples.
Researchers have developed two electromechanical patient simulators. These high-performance, cost-effective, patient simulators have received promising clinical feedback...
Researchers have developed two electromechanical patient simulators. These high-performance, cost-effective, patient simulators have received promising clinical feedback suggesting that these devices can mimic the behavior of a real patient by 1) generating a simulated behavior whose triggering and maintaining mechanism aligned with clinicians' experience and 2) recreating a relatively realistic haptic response of affected muscles. These training simulators will not only allow healthcare learners to gain practical experience more efficiently, but they also have the potential to standardize diagnostic procedures and enhance diagnosis accuracy and consistency by providing a relatively realistic, consistent, and scalable training environment for students, allowing learners to gain hands-on experience without the presence of human patients.
