Detection of the carotid artery lumen and bifurcation contours in ultrasound B-mode images

Detection of the carotid artery lumen and bifurcation contours in ultrasound B-mode images André M.F. Santos1(*), João Manuel R.S. Tavares1, Luísa Sousa1, Rosa Santos2, Pedro Castro2 and Elsa Azevedo2 1 Faculdade de Engenharia, Universidade do Porto, Portugal 2 Faculdade de Medicina, Universidade do Porto, Portugal Emails: [email protected], [email protected], [email protected], [email protected] Abstract A new algorithm is proposed for the correct identification of the lumen and bifurcation contours of the carotid artery in ultrasound B-mode images. The algorithm uses hipoechogenic characteristics to guide the lumen identification and echogenic characteristics to detect the artery bifurcation. The input image is preprocessed for speckle removal by an anisotropic diffusion filter and morphologic operators for image enhancement. Two initial contours are then automatically defined in the preprocessed image, one for the lumen identification and a second one to segment the bifurcation boundaries, which are used to initialize two Chan-vese level set models [1], [2], [3]. A set of B-mode images of the common carotid artery (CCA) was acquired using a GE Healthcare Vivid-e ultrasound scanner. All the images under evaluation included a part of the CCA and the bifurcation that separates the CCA into the internal carotid artery and external carotid artery. In order to achieve the highest contrast and lowest speckle noise level, the parameters of the scanner were defined differently for each image. We successfully apply our computational method based on cervical ultrasonography in the detection of the carotid artery lumen and bifurcation contours in all test ultrasound B-mode images. The main advantage of our method relies on the automatic identification of the carotid lumen, overcoming the limitations of the traditional methods. The 3D models of the carotid artery that can be built based on the contours detected by our method will be extremely important for better diagnosis, treatment plans and addressing practical clinical problems in carotid vascular diseases. This task has been currently addressed. REFERENCES [1] Rocha, R., Campilho, A., Silva, J., Azevedo, E., Santos, R., (2011). Segmentation of ultrasound images of the carotid using RANSAC and cubic splines. Computer methods and programs in biomedicine, 101(1), 94-106; [2] Molinari, F., Zeng, G., Suri, J. S., (2010). An integrated approach to computer-based automated tracing and its validation for 200 common carotid artery wall ultrasound images, J. Ultrasound Med., 29(3), 399-418; [3] Santos, A., Tavares, J., Sousa, L., Santos, R., Castro, P., Azevedo, E., (2012), Automatic segmentation algorithm for the lumen of the carotid artery in ultrasound B-mode images, 15th International Conference on Experimental Mechanics (ICEM15), Faculty of Engineering, University of Porto, Portugal, 22-27 July 2012