Automated Ultrasound Object Segmentation Using Combinatorial Active Contour Method

  • Anan Nugroho Universitas Negeri Semarang
  • Budi Sunarko Universitas Negeri Semarang
  • Hari Wibawanto Universitas Negeri Semarang
  • Anggraini Mulwinda Universitas Negeri Semarang
  • Anas Fauzi Universitas Negeri Semarang
  • Dwi Oktaviyanti Universitas Negeri Semarang
  • Dina Wulung Savitri Universitas Negeri Semarang


Active Contour (AC) is an algorithm widely used in segmentation for developing Computer-Aided Diagnosis (CAD) systems in ultrasound imaging. Existing AC models still retain an interactive nature. This is due to the large number of parameters and coefficients that require manual tuning to achieve stability. Which can result in human error and various issues caused by the inhomogeneity of ultrasound images, such as leakage, false areas, and local minima. In this study, an automatic object segmentation method was developed to assist radiologists in an efficient diagnosis process. The proposed method is called Automatic Combinatorial Active Contour (ACAC), which combines the simplification of the global region-based CV (Chan-Vese) model and improved-GAC (Geodesic Active Contour) for local segmentation. The results of testing with 50 datasets showed an accuracy value of 98.83%, precision of 95.26%, sensitivity of 86.58%, specificity of 99.63%, similarity of 90.58%, and IoU (Intersection over Union) of 82.87%. These quantitative performance metrics demonstrate that the ACAC method is suitable for implementation in a more efficient and accurate CAD system.

How to Cite
Anan Nugroho, Sunarko, B., Wibawanto, H., Mulwinda, A., Fauzi, A., Oktaviyanti, D., & Savitri, D. W. (2024). Automated Ultrasound Object Segmentation Using Combinatorial Active Contour Method. Jurnal Ilmu Komputer Dan Informasi, 17(2), 203-218.