Generation of Patient-Specific Cardiac Vascular Networks: a Hybrid Image-Based and Synthetic Geometric Model
A New Modeling Method to Characterize the Stance Control Function of Prosthetic Knee Joints
A new method is presented to characterize the function of lower-limb prosthetic stance control under mobility conditions associated with activities of daily living. The method is based on a model of the gait modes corresponding to finite stance control states. Empirical data from amputee and simulated gait were acquired using a custom built wearable instrument and input into the model. The modeling approach was shown to be robust, responsive and capable of accurate characterization of controller function under diverse of locomotor and prosthetic setup conditions.
Quantification and Analysis of Laryngeal Closure from Endoscopic Videos
We propose an automatic method to quantify laryngeal movements from laryngoscopic videos, to facilitate the diagnosis procedure. The proposed method analyses laryngoscopic videos, and delineates glottic opening, vocal folds, and supraglottic structures, using a deep learning-based algorithm. The segmentation results are quantified along the temporal dimension and processed using singular spectrum analysis (SSA), to extract information that can be used by the clinicians in diagnosis. The segmentation was validated on 400 images from 20 videos acquired using different endoscopic systems from different patients. Five clinical cases on patients have also been provided to showcase the final quantitative analysis result.
Smart Cell Culture Monitoring and Drug Test Platform Using CMOS Capacitive Sensor Array
Integrated Microfluidic CMOS or imCMOS has recently received significant interest, as a new paradigm in the design and implementation of chemical/biological analysis platforms, for life science applications. Among these applications, this research has focused on developing a novel imCMOS device for monitoring drug cytotoxicity. This device incorporated with polyelectrolyte layers consists of 8×8 capacitive sensors integrated on the same chip. With the potential to perform label free cellular analysis, the proposed platform opens an avenue to transit from traditional to smart cellular analysis techniques suitable for a variety of biological applications, in particular high throughput cell based drug testing.
Acousto-optic Catheter Tracking Sensor for Interventional MRI Procedures
Catheter tracking and guidance in the body is essential for interventional procedures. However, traditional catheters are invisible under magnetic resonance imaging (MRI). We present an acousto-optic sensor for tracking catheter position during interventional MRI. A coil antenna collects local MRI signal. In order to eliminate the RF induced heating, optical fiber is used to carry the MRI signal. An acousto-optic modulator based on fiber Bragg grating (FBG) is developed to convert the electrical signal from the antenna to optical signal to be carried by the fiber. Sensor was successfully tested for position detection in phantom under MRI.
Non-invasive Treatment Efficacy Evaluation for HIFU Therapy Based on Magneto-Acousto-Electrical Tomography
To ensure the therapeutic effect of HIFU therapy with minimized damage to surrounding tissues, a monitoring method for thermal ablation using the MAET technology is proposed based on the temperature-conductivity relation of tissues. With the distributions of acoustic pressure, temperature and electrical conductivity for a cylindrical model, real-time simulations of MAET signal demonstrated that two wave clusters can be generated by the sharp conductivity variation of HIFU ablation at >69 ˚C with a minimum axial interval of one wavelength. The favorable results provide a sensitive modality for non-invasive treatment efficacy evaluation during HIFU therapy and suggest potential applications in biomedical engineering.
Background Removal and Vessel Filtering of Non-Contrast Ultrasound Images of Microvasculature
A clutter removal method is proposed that utilizes spatiotemporal coherence of the ultrasound plane wave imaging data to significantly suppress tissue clutter signal obtained over extended ensembles. Nonlinear filtering via morphological operations and Hessian-based analysis are proposed to provide superb background rejection and vessel enhancement. This new imaging method, solely based on ultrasound, enables visualization of the small vessels that may find applications in both preclinical and clinical settings. In clinical applications, this method may provide a versatile tool for monitoring angiogenesis which may provide invaluable diagnostic and prognostic information.