A MHT-BASED ALGORITHM FOR PERFORMANCE ESTIMATION IN DT-MRI BAYESIAN TRACKING METHODS

L. M. San José Revuelta

2009

Abstract

This paper deals with the development of a recursive fuzzy inference system that can be applied to estimate the error probability of several tracking algorithms used in medical image processing systems. Specifically, we are interested in the fiber bundles estimation process (fiber tracking) in diffusion tensor (DT) fields acquired via magnetic resonance imaging (MRI). As tracking algorithm we have considered a variation of the Bayesian tracking scheme proposed by Friman and Westin. This paper studies the analogies between this tracking approach and a typical Multiple Hypotheses Tracing (MHT) system, for which fuzzy systems are closely related. This comparison leads to the development of a SAM (Standard Additive Model) fuzzy system that on-line estimates the certainty of the estimated fiber tracts. Its low computational load as well as its efficiency in very isotropic volumes are its main advantages.

References

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Paper Citation


in Harvard Style

San José Revuelta L. (2009). A MHT-BASED ALGORITHM FOR PERFORMANCE ESTIMATION IN DT-MRI BAYESIAN TRACKING METHODS . In Proceedings of the 6th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO, ISBN 978-989-674-000-9, pages 445-448. DOI: 10.5220/0002213204450448


in Bibtex Style

@conference{icinco09,
author={L. M. San José Revuelta},
title={A MHT-BASED ALGORITHM FOR PERFORMANCE ESTIMATION IN DT-MRI BAYESIAN TRACKING METHODS},
booktitle={Proceedings of the 6th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,},
year={2009},
pages={445-448},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002213204450448},
isbn={978-989-674-000-9},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 6th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,
TI - A MHT-BASED ALGORITHM FOR PERFORMANCE ESTIMATION IN DT-MRI BAYESIAN TRACKING METHODS
SN - 978-989-674-000-9
AU - San José Revuelta L.
PY - 2009
SP - 445
EP - 448
DO - 10.5220/0002213204450448