Automatic Segmentation of Abdominal Aortic Aneurism (AAA) By Using Active Contour Models

Rifki Kosasih


Abdominal aortic aneurysm (AAA) is a disease that is caused by dilation of the aortic wall. Dilation of the aortic wall will affect the size of the diameter of lumen and the aorta. In this study we use T1 and T2 images on 4 patients with AAA which generated from MR Imaging to calculate the diameter of the abdominal aortic aneurysm (AAA). To calculate the diameter of lumen and the aorta, the first step is image registration using Laplacian eigenmap method. After that we propose an automatic segmentation method on region of the aorta by using active contour models to get the contour of lumen and the aorta. The last step,  we calculate the diameter of lumen and the aorta by using contour of lumen and the aorta. In our experiment, active contour model is very good method for segmentation AAA. In the result, our proposed model give the accuracy rate of lumen is 96.41% and accuracy rate of aorta is 95.22%. 


Abdominal aortic aneurysm, MR Imaging, Laplacian Eigenmap, Active Contour Models, lumen

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. Beckman, J. A. (2006). Aortic aneurysms: pathophysiology, epidemiology, and prognosis in: M.A. Creager, V.J. Dzau, J. Loscalzo (Eds). Philadelphia : Elsevier Inc.

. Riminarsih, D., Karyati, C. M., Mutiara, A. B., Ernastuti., and Wahyudi, B. (2016). Sagittal Image Segmentation from Patients with Abdominal Aortic Aneurysms. TELKOMNIKA, 14(3), 1105-1112.

. Mussa, F. F. (2015). Screening for Abdominal Aortic Aneurysm. J Vasc Surg, 62(3), 774-778.

. Kosasih, R., Madenda, S., Karyati, C. M., and Lussiana. (2015). Determination the Optimal Position from T1 and T2 Weighted MR Imaging of the Abdominal Aortic Aneurysm. Adv. Sci. Eng. Med, 7(10), 915-919.

. Karyati, C. M. (2013). Rekonstruksi 4D (3D+Waktu) Citra Aliran Darah Pada Pasien Aneurisma Aorta Abdminalis dengan Kategori Thrombus dari Hasil Pemeriksaan MRI. PhD Thesis. Gunadarma University.

. Belkin, M., and Niyogi, P. (2003). Laplacian eigenmaps for dimensionality reduction and data representation. Neural Computation, 15(6), 1373-1396.

. Zhang, J., Xie, C., Song, L., Li, R., and Chen, H. (2016). Robust Image Segmentation Using LBP Embedded Region Merging. TELKOMNIKA, 14(1), 368-377.

. Kusanti, J., and Santosa, Y. Z. (2016). Comparison of Patterns Shapes and Patterns Texture for Identification of Malaria Parasites in Microscopic Image. Scientific Journal of Informatics, 3(2), 109-118.

. Chan, T. F., & Vese, L. A. (2001). Active Contours Without Edges. IEEE Transactions On Image Processing, 10(2), 266-277.

. Hou, L. (2014). Color Remote-Sensing Image Segmentation Based on Improved Region Filter. Journal of Multimedia, 9(9), 1128-1134.

. Kashyap, R., and Tiwari, V. (2017). Energy-Based Active Contour method for Image Segmentation. Int. J. Electronic Healthcare, 9(2), 210-225.

. Tjandrasa, H., Wijayanti, A., and Suciati, N. (2012). Optic Nerve Head Segmentation Using Hough Transform and Active Counturs. TELKOMNIKA, 10(3), 531-536.

. Zhang, K.., Zhang, L., Song, H., and Zhou, W. (2010). Active Contours with Selective Local or Global Segmentation: A New Formulation and Level Set Method. Image and Vision Computing, 28(4), 668-676.

. Mumford, D., and Shah, J. (1989). Approximation by piecewise smooth functions and associated variational problems. Commun. Pure Appl. Math, 42, 577–685.

. Goyal, M. (2011). Morphological Image Processing. International Journal of Computer Science and Technology, 2, 161-165.

. Shih, F. Y. (2009). Image Processing and Mathematical Morphology. New York: CRC Press.

. Lestari, D. P., Madenda, S., Ernastuti., and Wibowo, E. P. (2017). Comparison of Three Segmentation Methods for Breast Ultrasound Images Based on Level Set and Morphological Operations. International Journal of Electrical and Computer Engineering (IJECE), 7(1), 383-391.

. Kumar, B. A., Jairam, R., Arkatkar, S. S., and Vanajakshi, L. (2019). Real time bus travel time prediction using k-NN classifier. Int. J. Transp. Res, 11(7), 362-372.



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