Abstract
The use of medical images in diagnosing and analyzing various cases in the medical field is commonly used. In certain cases, the image used is not limited to two-dimensional images, but sometimes requires the use of three-dimensional images. CT scan image is an image that has several image slices that can be reconstructed into a three-dimensional image. In the reconstruction process, segmentation plays an important role to get a good reconstruction result and reduce the resulting noise. This study aims to develop a method used in CT scan image segmentation, with the hope that it can simplify the diagnosis process performed by doctors using two-dimensional images or those that have been constructed into three-dimensional images. The main method developed is the Otsu Thresholding method based on the threshold value, which is combined with the Hounsfield unit (HU) value which will be the input for the segmentation process. The image used is a thorax CT scan image with the final goal to get the results of heart segmentation. The results obtained based on the calculation of balanced accuracy for the 30 data tested had an average of 72.54%. The highest result of balanced accuracy for heart segmentation was obtained by data 4 of 77.43%, while the lowest result was obtained by data 29 of 69.1%.
Published Version
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