Abstract
The use of classifier-based object detection has found to be a promising approach in medical anatomy detection. In ultrasound images, the detection task is very challenging due to speckle, shadows and low contrast characteristic features. Typical detection algorithms that use purely intensity-based image features with an exhaustive scan of the image (sliding window approach) tend not to perform very well and incur a very high computational cost. The proposed approach in this paper achieves a significant improvement in detection rates while avoiding exhaustive scanning, thereby gaining a large increase in speed. Our approach uses the combination of local features from an intensity image and global features derived from a local phase-based image known as feature symmetry. The proposed approach has been applied to 2384 two-dimensional (2D) fetal ultrasound abdominal images for the detection of the stomach and the umbilical vein. The results presented show that it outperforms prior related work that uses only local or only global features.
Chapter PDF
Similar content being viewed by others
Keywords
References
Salomon, L.J., et al.: Feasibility and reproducibility of an image-scoring method for quality control of fetal biometry in the second trimester. Ultrasound in O&G 27, 34–40 (2006)
Viola, P., Jones, M.J.: Robust Real-Time Face Detection. International Journal of Computer Vision 57, 137–154 (2004)
Karavides, T., Leung, K.Y.E., Paclik, P., Hendriks, E.A., Bosch, J.G.: Database guided detection of anatomical landmark points in 3D images of the heart. In: 2010 IEEE International Symposium on Biomedical Imaging, Rotterdam, pp. 1089–1092 (2010)
Rahmatullah, B., Sarris, I., Papageorghiou, A., Noble, J.A.: Quality control of fetal ultrasound images: Detection of abdomen anatomical landmarks using AdaBoost. In: 2011 IEEE International Symposium on Biomedical Imaging, Chicago, IL, pp. 6–9 (2011)
Rajpoot, K., Vicente, V.V., Noble, J.A.: Local-phase based 3D boundary detection using monogenic signal and its application to real-time 3-D echocardiography images. In: 2009 IEEE International Symposium on Biomedical Imaging, Boston, MA, pp. 783–786 (2009)
Grau, V., Noble, J.A.: Adaptive Multiscale Ultrasound Compounding Using Phase Information. In: Duncan, J.S., Gerig, G. (eds.) MICCAI 2005. LNCS, vol. 3749, pp. 589–596. Springer, Heidelberg (2005)
Kovesi, P.: Symmetry and Asymmetry From Local Phase. In: Tenth Australian Join Conference on Artificial Intelligence, Brisbane, pp. 185–190 (1997)
Felsberg, M., Sommer, G.: The monogenic signal. IEEE Transactions on Signal Processing 49, 3136–3144 (2001)
Freund, Y., Schapire, R.E.: A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting. Journal of Computer & System Sciences 55, 119–139 (1997)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Rahmatullah, B., Papageorghiou, A.T., Noble, J.A. (2012). Integration of Local and Global Features for Anatomical Object Detection in Ultrasound. In: Ayache, N., Delingette, H., Golland, P., Mori, K. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2012. MICCAI 2012. Lecture Notes in Computer Science, vol 7512. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33454-2_50
Download citation
DOI: https://doi.org/10.1007/978-3-642-33454-2_50
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-33453-5
Online ISBN: 978-3-642-33454-2
eBook Packages: Computer ScienceComputer Science (R0)