STUDY OF THE EFFECT OF ADAPTIVE STATISTICAL ITERATIVE RECONSTRUCTION-V (ASIR-V) ON NOISE ON CT SCAN IMAGES FROM AAPM PHANTOMS

• Main Author: Hanifa Dhiyani, Alyssa
• Format: Final Project
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/83536
• Institution: Institut Teknologi Bandung

Noise is one of the image quality parameters of Computed Tomography (CT) scan which is influenced by several parameters, such as tube current, tube voltage, and reconstruction algorithm used in image processing. This research aims to analyze noise produced based on the influence of ASiR-V levels, tube current variations, and number of Region of Interest (ROI) in determining the optimum number of ROI. Data was processed using water phantom on the AAPM CT Performance Phantom, Noise Power Spectrum (NPS) method, and automatic calculations using IndoQCT software. Each CT scan image has tube current variations of 250, 300, 350, 400, and 450 mAs, ASiR-V level variations of 0%, 20%, 40%, 60%, 80%, and 100%, and the number of ROIs 1, 3, and 5. From the IndoQCT, the mean, standard deviation, and NPS curve were obtained then processed with OriginLab software and polynomial smoothing to get maximum value of NPS (????????2????????2) and spatial frequency (?????????1). In analyzing noise, the parameters used are maximum value of NPS for variations in ASiR-V levels and standard deviation for variations in tube current. The results are presented in a linear curve, line equation, and ????2 that can be analyzed based on gradient of the curve. The results obtained were steeper gradients in varying tube current values and low ASiR-V levels. The ASiR-V level in each ROI variation and the tube current that produces low noise will be used in the analysis to determine the optimum number of ROIs based on the maximum NPS and ????2 value.