Microembolic signal characterization by transcranial Doppler imaging

Transcranial Doppler detection and monitoring of cerebral microemboli have provided a new and useful method to diagnose, and potentially to foresee, increased risk of stroke. Until now, however, the assessment of this method in routine clinical practice has been limited by the lack of a reliable automatic differentiation between solid and gaseous microemboli. The aim of this work is the definition of a clinical diagnostic support procedure for the automatic recognition of emboli of different composition. The proposed method makes use of image processing techniques and neural algorithms for data interpretation and performs a feature-based analysis of the ultrasonographic images showing the microembolic events. Application to clinical cases selected by expert neurologists for their clinical relevance and experimental results have showed effective operability of the developed procedure.