Radiation monitoring systems able to accurately track the radiation dose received by the patient and the medical staff during interventional fluoroscopy can be used to minimize the likelihood and severity of radiation-induced skin injuries and estimate the accumulated organ doses. We describe a method to monitor doses in real time using automatic sensors in the imaging room and a CPU-accelerated computer simulator. The Monte Carlo simulation code MC-GPU is used to estimate patient and staff doses due to primary and scattered radiation, along with the associated statistical uncertainties. The geometrical configuration of the irradiation is automatically determined and updated using data from a depth camera that tracks the location and posture of each person in the imaging room. A virtual x-ray source graphical interface is used to manually trigger the simulations. The implemented computational framework separates the simulation of the x-ray transport through the patient and the operator bodies into two coupled, sequential simulations. The initial simulation uses the patient anatomy and a c-arm source model with a collimated cone beam emitted from a point focal spot. During this simulation a large phase space file with the energy, position and direction of x rays scattered in the direction of the operator is created. The phase space file is then used as the input radiation source for the following simulation with the operator anatomy model. Particle recycling is employed as a variance reduction technique to maximize the information obtained from the limited number of particles scattered towards the operator. For a typical image acquisition, a patient skin dose map can be displayed at the operator's monitor within 10 seconds with a peak skin dose error below 1%. This work demonstrates that a dose monitoring system based on accurate Monte Carlo simulations can be used to estimate in real-time the average and peak organ doses for both the patient and the staff in interventional fluoroscopy, and provide timely information regarding possible overdoses while the imaging procedure is being performed.
KEYWORDS: Visualization, Signal to noise ratio, Imaging systems, Seaborgium, 3D image processing, Image visualization, Data modeling, 3D displays, Eye, Medical imaging
We present a computational stereoscopic observer approach inspired by the mechanisms of stereopsis in human
vision that makes decisions based on a set of image pairs. Our stereo observer is constrained to a left and a right
image generated using a visualization operator (ray tracing) to render simulated voxel datasets. We present
the formulation of the observer based on model observer theory and discuss issues regarding simulated data
generation and processing for this approach. The applicability of this observer extends to stereoscopic displays
in the areas of entertainment, industrial, and medical imaging applications.
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