CT-Scan Image Optimization with Tube Current Variation in Some Kernel Filters Based on Signal to Noise Ratio (SNR) Value

Abstract

Computed Tomography Scan (CT-Scan) is a diagnostic tool that determines human organs using x-rays, contemporary tomography, and computational procedures. As a result, an optimal image is required in order for the object examination to be appropriately diagnosed. Based on the Signal to Noise Ratio (SNR) value, this study attempts to optimize CT-Scan image with tube Current Variations on Several Kernel Filters. The goal is to understand the influence of variations in tube currents on numerous filter kernels on image quality on CT-Scan based on SNR, as well as the value of tube current and kernel type. This study begins by scanning the water phantom with variations of tube currents of 150 mA, 200 mA, 250 mA, and 300 mA, a total of three scans for each tube current variation to obtain 12 raw data. Furthermore, the filter step employs two types of kernel filters, soft and edge, for each raw data. The filtered data is searched for Region of Interest (ROI) on the object and background in order to obtain the signal value (mean) and noise (standard deviation) in the image, which can then be used to determine the SNR value. The SNR value demonstrates that differences in tube currents and kernel filters have an impact on the CT-Scan image’s quality. The use of the Soft kernel filter and a tube current of 300 mA produced the best results with the maximum SNR.