International Journal of Computer Vision
IEEE Transactions on Image Processing
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Boundary detection has a relevant importance in locomotor system ecographies, mainly because some illnesses and injuries can be detected before the first symptoms appear. The images used show a great variety of textures as well as non clear edges. This drawback may result in different contours depending on the person who traces them out and different diagnoses too. This paper presents the results of applying the geodesic active contour and other boundary detection techniques in ecographic images of Aquiles tendon, such as morphological image processing and active contours. Other modifications to this algorithm are introduced, like matched filtering. In order to upgrade the smoothness of the final contour, morphological image processing and polynomial interpolation has been used with great results. Actually, the automatization of boundary detection improves the measurement procedure, obtaining error rates under ±10%.