<![CDATA[Segmentation is the process of separating parts of objects from the background by dividing images that have different object intensities with each other such as in imaging of body parts. Active contour segmentation was used for medical imaging that resistant to noise around objects. This study used 5 chest X-Ray images, specifically to the lungs with a grayscale format measuring 256 x 256 pixels, through the preprocessing process and filtering a Gaussian filter, each image was inputted to the R2015a version of the matlab GUI program. Then the segmentation had done by using the active contour method. In this method a curve in the form of a small circle was placed on the edge of object to be segmented. The curve will move according to the shape of the outer edge of the lung based on the values of active contour parameters such as Alpha, Beta, Gamma, Kappa, WEline, WEdge, WEterm and Iteration. Validation was done by using the ROC (Receiver Operating Characteristic) method and were obtained an average percentage with an accuracy value of 96.26%, a specificity of 96.47% and a sensitivity of 76.54%.]]>
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