Image Quality optimization using an x-ray spectra model based optimization method

Several x-ray parameters must be optimized to deliver exceptional fluoroscopic and radiographic x-ray Image Quality (IQ) for the large variety of clinical procedures and patient sizes performed on a cardiac/vascular x-ray system. The optimal choice varies as a function of the objective of the medical exam, the patient size, local regulatory requirements, and the operational range of the system. As a result, many distinct combinations are required to successfully operate the x-ray system and meet the clinical imaging requirements. Presented here, is a new, configurable and automatic method to perform x-ray technique and IQ optimization using an x-fay spectral model based simulation of the x-ray generation and detection system. This method incorporates many aspects/requirements of the clinical environment, and a complete description of the specific x-ray system. First, the algorithm requires specific inputs: clinically relevant performance objectives, system hardware configuration, and system operational range. Second, the optimization is performed for a Primary Optimization Strategy versus patient thickness, e.g. maximum contrast. Finally, in the case where there are multiple operating points, which meet the Primary Optimization Strategy, a Secondary Optimization Strategy, e.g. to minimize patient dose, is utilized to determine the final set of optimal x-ray techniques.