Real-Time Gpu-Based 3D Ultrasound Reconstruction and Visualization
Ultrasound scanning is frequently used in medical practice because it is a non-invasive, safe and low-cost solution (vs. CT or MR). However, conventional ultrasound probes only provide 2D scans. 3D ultrasound reconstruction builds 2D scans into 3D volumes of the patient's internals. However, the 3D reconstruction process is computationally demanding and includes processing millions of picture and volume elements. This process can currently take minutes or even hours on conventional systems. It is very desirable to reconstruct ultrasound images in real-time to guide surgeons doing surgery. In this thesis, we manage to achieve this by utilizing the parallel processing power of GPUs with hundreds of computing cores. Our novel optimized methods take advantage of this power in order to perform entire volume reconstructions in only fractions of a second.
Automobile crashes are the largest cause of death for pregnant females and the leading cause of traumatic fetal injury mortality in the United States. Research for pregnant occupant safety utilizing computational models is limited by available pregnant tissue data. This study collected experimental data from biaxial tissue tests on pregnant uterine tissue at a dynamic rate. Experimental tests were conducted on pregnant porcine uterus which was chosen as a surrogate for the human pregnant uterus. Biaxial dynamic tensile tests were performed. The specimen was loaded at a rate of 0.7 strains per second to match the uterine strain rate in a motor vehicle crash. Experimental results include peak stresses and peak strains for the pregnant uterine tissue in tension. The results can be implemented in pregnant occupant models to evaluate the uterine tissue response to impact loading scenarios.