title: Detection of Doppler Microembolic Signals Using High Order Statistics.
abstract: Robust detection of the smallest circulating cerebral microemboli is an efficient way of preventing strokes, which is second cause of mortality worldwide. Transcranial Doppler ultrasound is widely considered the most convenient system for the detection of microemboli. The most common standard detection is achieved through the Doppler energy signal and depends on an empirically set constant threshold. On the other hand, in the past few years, higher order statistics have been an extensive field of research as they represent descriptive statistics that can be used to detect signal outliers. In this study, we propose new types of microembolic detectors based on the windowed calculation of the third moment skewness and fourth moment kurtosis of the energy signal. During energy embolus-free periods the distribution of the energy is not altered and the skewness and kurtosis signals do not exhibit any peak values. In the presence of emboli, the energy distribution is distorted and the skewness and kurtosis signals exhibit peaks, corresponding to the latter emboli. Applied on real signals, the detection of microemboli through the skewness and kurtosis signals outperformed the detection through standard methods. The sensitivities and specificities reached 78% and 91% and 80% and 90% for the skewness and kurtosis detectors, respectively.
authors.affiliation: Université François Rabelais de Tours, UMR Imagerie et Cerveau Inserm U930, Tours, France; Department of Physics and Electronics, Faculty of Sciences I, Lebanese University, Beirut, Lebanon.
authors.forename: Maroun
authors.initials: M
authors.lastname: Geryes
authors.affiliation: Université François Rabelais de Tours, UMR Imagerie et Cerveau Inserm U930, Tours, France.
authors.forename: Sebastien
authors.identifier: 0000-0002-7097-7533
authors.initials: S
authors.lastname: Ménigot
authors.affiliation: Clarivate Analytics, Dubai, UAE.
authors.forename: Walid
authors.initials: W
authors.lastname: Hassan
authors.affiliation: Department of Physics and Electronics, Faculty of Sciences I, Lebanese University, Beirut, Lebanon.
authors.forename: Ali
authors.initials: A
authors.lastname: Mcheick
authors.affiliation: Department of Physics and Electronics, Faculty of Sciences I, Lebanese University, Beirut, Lebanon.
authors.forename: Jamal
authors.identifier: 0000-0003-0256-905X
authors.initials: J
authors.lastname: Charara
authors.affiliation: Université François Rabelais de Tours, UMR Imagerie et Cerveau Inserm U930, Tours, France.
authors.forename: Jean-Marc
authors.identifier: 0000-0002-2356-885X
authors.initials: JM
authors.lastname: Girault
mesh_terms: D000465:Algorithms; D016477:Artifacts; D016208:Databases, Factual; D004867:Equipment Design; D005583:Fourier Analysis; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D020766:Intracranial Embolism / Q000000981:diagnostic imaging*; D015233:Models, Statistical; D010363:Pattern Recognition, Automated; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted; D012984:Software; D017585:Ultrasonography, Doppler, Transcranial