Automatic Embolus Detection by a Neural Network | Zendy

Vendel Kemény | Zendy; Dirk W. Droste | Zendy; Stefan Hermes | Zendy; Darius G. Nabavi | Zendy; Gernot SchulteAltedorneburg | Zendy; Mario Siebler | Zendy; E. Bernd Ringelstein | Zendy

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Automatic Embolus Detection by a Neural Network

Author(s) -

Vendel Kemény,

Dirk W. Droste,

Stefan Hermes,

Darius G. Nabavi,

Gernot SchulteAltedorneburg,

Mario Siebler,

E. Bernd Ringelstein

Publication year - 1999

Publication title -

stroke

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.397

H-Index - 319

eISSN - 1524-4628

pISSN - 0039-2499

DOI - 10.1161/01.str.30.4.807

Subject(s) - medicine , embolus , artifact (error) , transcranial doppler , artificial neural network , radiology , ultrasound , false positive paradox , embolism , stroke (engine) , cardiology , artificial intelligence , computer science , mechanical engineering , engineering

Embolus detection using transcranial Doppler ultrasound is a useful method for the identification of active embolic sources in cerebrovascular diseases. Automated embolus detection systems have been developed to reduce the time of evaluation in long-term recordings and to provide more "objective" criteria. The purpose of this study was to evaluate the critical conditions of automated embolus detection by means of a trained neural network (EMBotec V5.1 One, STAC GmbH, Germany).

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