Abstract
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%.
Access provided by Autonomous University of Puebla. Download to read the full chapter text
Chapter PDF
Similar content being viewed by others
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
References
González, R.C., Woods, R.E.: Digital Image Processing. Prentice Hall, Englewood Cliffs (2002)
Liang, J., McInerney, T., Terzopoulosd, D., Liang, J., McInerney, T., Terzopoulos, D.: United snakes. Medical Image Analysis 10, 133–215 (2006)
Huete, V.M.: Implementación en Matlab de modelos deformables en el dominio de la frecuencia. Master’s thesis, ETSIT: Escuela Técnica de Ingeniería de Telecomunicación (February 2005)
Caselles, V., Kimmel, R., Sapiro, G.: Geodesic active contours. International Journal of Computer Vision 22(1), 61–79 (1997)
Payá, J.J.M., Díaz, J.R., del Baño Aledo y otros, M.E.: Estudio de fiabilidad intra e interobservador en la medición del perímetro del tendón de aquiles en un corte ecográfico transversal
Goldenberg, R., Kimmel, R., Rivlin, E., Rudzsky, M.: Fast geodesic active contours. IEEE Transactions On Image Processing 10(10) (October 2001)
Southwest Jiaotong University: Texture Image Segmentation Using Without Re-initialization Geodesic Active Contour Model, Chengdu, P.R. China, Southwest Jiaotong University (October 2007)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Bastida-Jumilla, MC., Morales-Sánchez, J., Verdú-Monedero, R., Larrey-Ruiz, J., Sancho-Gómez, J.L. (2009). Measurements over the Aquiles Tendon through Ecographic Images Processing. In: Mira, J., Ferrández, J.M., Álvarez, J.R., de la Paz, F., Toledo, F.J. (eds) Bioinspired Applications in Artificial and Natural Computation. IWINAC 2009. Lecture Notes in Computer Science, vol 5602. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02267-8_1
Download citation
DOI: https://doi.org/10.1007/978-3-642-02267-8_1
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-02266-1
Online ISBN: 978-3-642-02267-8
eBook Packages: Computer ScienceComputer Science (R0)