Segmentasi Citra CT-Scan Pada Stroke Menggunakan Metode Algoritma K-Means Clustering dan Thresholding di Rumah Sakit Samarinda Medika Citra - Payon, Fransiska Lipa (Universitas Padjadjaran, 2024)
Strokes examination using CT-Scan is a technique that produces 3D images of the brain without having to do surgery. The purpose of this study was to determine the results of strokes image segmentation using the K-Means Clustering and the Thresholding algorithm method at Samarinda Medika Citra Hospital, and to determine the results of the evaluation conducted by the Radiologist on the results of strokes image segmentation. Data processing in this study was carried out with qualitative techniques, i.e., observing and also evaluating the results of strokes image segmentation. The evaluation results for K-Means Clustering segmentation using k=3 are 70% correct. The evaluation results of the Thresholding method are 100% correct using the threshold value is 100-180. Based on the results of this study, the results of the Thresholding segmentation are more recommended for evaluation because they get the best threshold value.Keywords: K-Means Clustering, Strokes, Segmentation, Thresholding