Abstract
This paper aims at developing an ultrasound-based diagnostic measure which quantifies plaque activity, that is, the likelihood of the asymptomatic lesion to produce neurological symptoms. The method is rooted on the identification of an “active” plaque profile containing the most relevant ultrasound parameters associated with symptoms. This information is used to build an Enhanced Activity Index (EAI) which considers the conditional probabilities of each relevant feature belonging to either symptomatic or asymptomatic groups. This measure was evaluated on a longitudinal study of 112 asymptomatic plaques and shows high diagnostic power. In particular, EAI provides correct identification of all plaques that developed symptoms while giving a small number of false positives. Results suggest that EAI could have a significant impact on stroke prediction and treatment planning.
This work was supported by project the FCT (ISR/IST plurianual funding) through the PIDDAC Program funds.
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Seabra, J., Pedro, L.M., Fernandes e Fernandes, J., Sanches, J. (2011). Ultrasound Plaque Enhanced Activity Index for Predicting Neurological Symptoms. In: Vitrià, J., Sanches, J.M., Hernández, M. (eds) Pattern Recognition and Image Analysis. IbPRIA 2011. Lecture Notes in Computer Science, vol 6669. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21257-4_23
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DOI: https://doi.org/10.1007/978-3-642-21257-4_23
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