Improving the Quality of CT Images of Stroke Patients Using the SSDE and K-Means Segmentation in the Radiology Installation of RSUD A.W. Sjahranie Samarinda - Putri, Erlinda Ratnasari; Payon, Fransiska Lipa; Missinychrista, Ronel Arida; Putri, Devina Rayzy Perwitasari Sutaji; Wardani, Pratiwi Sri; Subagiada, Kadek (Lambung Mangkurat University Press, 2024)
Stroke examination using a CT scan is a technique that produces 3D brain images without having to do surgery. The purpose of this study was to determine the dose received by each patient who underwent a CT-scan procedure and to improve the image quality of the results. Optimization of the dose for each patient is based on a comparison between the calculated SSDE value and the DRL in the form of CTDIvol and DLP, which are implemented in Indonesia. Improving the quality of CT-Scan images through digital processing using the segmentation method to determine the stroke area. The method used is K-Means segmentation. The results obtained for the SSDE value are the dose received by the patient which is higher than the dose issued by the device or the value. However, the SSDE, CTDIvol, and DLP values are still below the DRL standard range set by BAPETEN, so they are still within the safe inspection threshold. The average CTDIvol value, which is the output dose value of the device from 22 patients, was 41.84 mGy and the 75th percentile value was 42.7 mGy. The average DLP value is 1054.08 mGy.cm and the 75th percentile value of the DLP value is 964.13 mGy.cm. The average value of the SSDE value which is the value of the dose received by the patient is 43.39 mGy and the 75th percentile value is 42.440 mGy. Based on these results, the value of the dose received by the patient is higher than the value of the dose issued by the device. Segmentation using the K-Means method with the number of clusters k = 3 produces an accuracy of 86.3%. This means that the patient receives a dose of CT-Scan radiation within safe limits and his image can be processed properly, as evidenced by the high success of the segmentation process.