The aim of this work was the definition of a method devoted to the automated recognition of different composition of cerebral microemboli. The developed diagnostic procedure made use of a feature-based analysis of ultrasonographic images containing the characteristic microembolic signals. The images were acquired with a transcranial Doppler and classified using a hierarchical neural network. The proposed procedure was tested on clinical cases selected by expert neurologists for their relevance, and experimental results showed its reliability.

Automatic recognition and classification of cerebral microemboli in ultrasound images

Colantonio S;Salvetti O;Sartucci F
2005

Abstract

The aim of this work was the definition of a method devoted to the automated recognition of different composition of cerebral microemboli. The developed diagnostic procedure made use of a feature-based analysis of ultrasonographic images containing the characteristic microembolic signals. The images were acquired with a transcranial Doppler and classified using a hierarchical neural network. The proposed procedure was tested on clinical cases selected by expert neurologists for their relevance, and experimental results showed its reliability.
2005
Istituto di Scienza e Tecnologie dell'Informazione "Alessandro Faedo" - ISTI
Vision and Scene Understanding
Hierarchical Neural Networks
Microemboli Classification
Image Analysis
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/79623
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