<![CDATA[CT scanning is a medical imaging technique that allows detailed visualization of structures within the body using X-ray radiation. The pixel intensity in the image is interpreted in Hounsfield Units (HU), which measure the relative density of tissue compared to water. WW and WL are two important parameters in adjusting the visualization of CT scan images, allowing radiologists to optimize the display of various tissue structures. WW is the middle value of the selected HU range. This value determines the grayscale intensity that is the center of the image contrast range. WL in tissue with a certain density, such as distinguishing between brain tissue and lesions or edema. The purpose of this study is to optimize the use of parameters to improve image quality and diagnostic accuracy and determine the optimal WW and WL. This research supports secondary transformation in the health care system, in improving the quality of clinical services through innovation in diagnostic technology.This research is an experimental study. Direct measurements were made of variations in 10 window width values and 3 window level values. After data collection, three radiologists assessed the data using a questionnaire. A kappa test was performed to assess the agreement or similarity of observer perceptions in assessing the questionnaire. Data analysis was performed using the Kolmogorov-Sprinov test to determine the appropriate test. The normality test yielded a p-value > 0.05, indicating that the data were normally distributed.The Kappa test results of 0.82 with p <0.001 indicate that there is a very good level of agreement or agreement between observers in assessing the quality of CT Scan images. The Kolmogorov-Smirnov results show that the data distribution is normal with a p value = 0.120 (p > 0.05), thus fulfilling the requirements for parametric testing. The results of the Paired T-Test show differences in image quality between WW and WL. Window Width at 95 with Window Level 35 is proven to provide the most optimal image quality and produces the highest score (mean = 4.5). And shows better contrast between the area ofbleeding and normal brain tissue, so that bleeding can be clearly identified. The clarity of brain anatomy is also better seen compared to wider or narrower WW variations. In addition, the noise level is relatively low, so it does not interfere with the radiologist's interpretation in assessing the image.]]>
Copyrights © 2025
