Abstract
Knowledge Based Imaging is suggested as a method to distinguish blood from tissue signal in transthoracial echocardiography. Parametric model for the autocorrelation functions for turbulent blood flow and slowly moving tissue are augmented for in this paper. The model also includes the presence of stationary clutter noise and system white noise. Knowledge Based Imaging utilizes the maximum likelihood function to classify blood and tissue signal. In amplitude imaging blood and tissue are separated by their difference in signal powers. This effect is also present in Knowledge Based Imaging. In addition, this method utilizes the fact that blood flow is turbulent and moves faster than tissue. Some images of Knowledge Based Imaging with different parameter settings are visually compared with Second-Harmonic Imaging, Fundamental Imaging and Bandwidth Imaging [1].
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Hovda, S., Rue, H., Olstad, B.: Bandwidth of the ultrasound doppler signal to distinguish blood from tissue signal in the left ventricle. In: Proceedings of Medical Imaging and Informatics (MIMI) (2007)
Angelsen, B.A.: 7.4,9,3, 10.4. In: Ultrasound Imaging Wawes, Signals and Signal Processing, Emantec, Trondheim, Norway (2000)
Torp, H.: Clutter rejection filters in color flow imaging a theoretical approach. IEEE Transactions on Ultrasonics, Ferroelectriscs. and Frequency Control 44, 417–424 (1997)
Torp, H., Kristoffersen, K., Angelsen, B.A.J.: Autocorrelation techniques in color flow imaging: Signal model and statistical properties of the autocorrelation estimates. IEEE Transactions on Ultrasonics, Ferroelectriscs. and Frequency Control (1994)
Heimdal, A., Torp, H.: Detecting small blood vessels in colorflow ultrasound imaging: a statistical approach. IEEE Transactions on Ultrasonics, Ferroelectriscs. and Frequency Control (1999)
Angelsen, B.A.J.: A theoretical study of the scattering of ultrasound from blood. IEEE Trans. Biomed. Eng. 27(2), 61–67 (1980)
Schoephoerster, C., Chandran, K.B.: Velocity and turbulence measurements past mitral valve prostheses in a model left ventricle. Journal of Biomechanics 24(7), 549–562 (1991)
Trees, H.L.V.: Detection, Estimation, and Modulation Theory, vol. 1. John Wiley and Sons, Inc., Chichester (1968)
An, L.T.H., Tao, P.D.: A branch and bound method via d.c. optimization algorithms and ellipsoidal technique for box constrained nonconvex quadratic problems. Journal of Global Optimization 13(2), 171–206 (1998)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Hovda, S., Rue, H., Olstad, B. (2008). New Doppler-Based Imaging Method in Echocardiography with Applications in Blood/Tissue Segmentation. In: Gao, X., Müller, H., Loomes, M.J., Comley, R., Luo, S. (eds) Medical Imaging and Informatics. MIMI 2007. Lecture Notes in Computer Science, vol 4987. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-79490-5_26
Download citation
DOI: https://doi.org/10.1007/978-3-540-79490-5_26
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-79489-9
Online ISBN: 978-3-540-79490-5
eBook Packages: Computer ScienceComputer Science (R0)