Accelerated partial separable model using dimension-reduced optimization technique for ultra-fast cardiac MRI

Objective. Imaging dynamic object with high temporal resolution is challenging in magnetic resonance imaging (MRI). Partial separable (PS) model was proposed to improve the imaging quality by reducing the degrees of freedom of the inverse problem. However, PS model still suffers from long acquisition time and even longer reconstruction time. The main objective of this study is to accelerate the PS model, shorten the time required for acquisition and reconstruction, and maintain good image quality simultaneously. Approach. We proposed to fully exploit the dimension reduction property of the PS model, which means implementing the optimization algorithm in subspace. We optimized the data consistency term, and used a Tikhonov regularization term based on the Frobenius norm of temporal difference. The proposed dimension-reduced optimization technique was validated in free-running cardiac MRI. We have performed both retrospective experiments on public dataset and prospective experiments on in-vivo data. The proposed method was compared with four competing algorithms based on PS model, and two non-PS model methods. Main results. The proposed method has robust performance against shortened acquisition time or suboptimal hyper-parameter settings, and achieves superior image quality over all other competing algorithms. The proposed method is 20-fold faster than the widely accepted PS+Sparse method, enabling image reconstruction to be finished in just a few seconds. Significance. Accelerated PS model has the potential to save much time for clinical dynamic MRI examination, and is promising for real-time MRI applications.Comment: 23 pages, 11 figures. Accepted as manuscript on Physics in Medicine & Biolog

Smartphone-based systems for mobile infectious disease detection and epidemiology

Infectious diseases remain a serious public health challenge worldwide and are the leading cause of death in many developing countries. The rapid detection of pathogens is vital for the control and prevention of the infectious diseases. New tools are needed to enable rapid detection, identification, and reporting of infectious viral and microbial pathogens in a wide variety of point-of-care applications that impact human and animal health. With the rapid development of mobile technologies, mobile devices have provided a novel and effective approach to identify and report infectious diseases. In this work, two types of smartphone-based detection platforms are developed for mobile infectious disease detection. The first one is for the detection of human immunodeficiency virus. The second one is for the multiplexed detection of nucleic acids of pathogens for equine respiratory infections. Both platforms utilize a smartphone camera as the sensor in conjunction with a handheld cradle that interfaces the phone with a microchip for the on-chip nucleic acid testing of infectious diseases. This work provides a mobile, simple and inexpensive capability for clinicians to perform infectious disease diagnostics, and it represents a significant stride towards a practical solution to the infectious disease diagnostics at resource-limited settings.Ope