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 makes use of a features-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 has been tested on clinical cases selected by expert neurologists for their relevance and experimental results have showed its reliability.
Automatic recognition and classification of cerebral microemboli in ultrasound images
Colantonio S;Salvetti O;
2004
Abstract
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 makes use of a features-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 has been tested on clinical cases selected by expert neurologists for their relevance and experimental results have showed its reliability.File in questo prodotto:
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Descrizione: Automatic recognition and classification of cerebral microemboli in ultrasound images
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