Abstract
MRI image evaluation of cystic ovarian neoplasms was done manually and is generally carried out by Radiologists using a manual technique called linear measurement. This technique has some weaknesses, including being considered a rough calculation estimate because measurements are made on only one largest slice and are vulnerable to subjectivity factors. This research applied a digital image processing program based on Matlab using a segmentation process and active contour Laplacian of Gaussian (LoG) in the measurement and calculation of the volume of cystic ovarian neoplasms. Analyze the differences in measurement results and find out which technique is better in the calculation of cystic ovarian neoplasm volume between techniques of linear measurement and techniques of active contour Laplacian of Gaussian (LoG). The research was done with 32 images of abdominal-pelvic MRI images with clinical cystic ovarian neoplasms, and measurements and calculations of the volume of cystic ovarian neoplasms were carried out using the technique linear measurement and active contour Laplacian of Gaussian (LoG). Measurement and calculation are done by Radiologists as an observer with data analysis using statistical processing. Analysis of MRI images of abdominal-pelvic MRI images with clinical cystic ovarian neoplasms using linear measurement and active contour Laplacian of Gaussian (LoG) techniques showed a difference with a p-value of 0.004 (p<0.05). The results of measurements using the active contour laplacian of the Gaussian technique are better than the linear measurement, as indicated by the higher mean rank of the active contour laplacian of Gaussian, which was 17.50 (higher than the linear measurement value of 13.50).
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