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Medical & Biological Engineering & Computing

, Volume 55, Issue 10, pp 1787–1797 | Cite as

Discrimination between emboli and artifacts for outpatient transcranial Doppler ultrasound data

  • Blaise Kévin GuépiéEmail author
  • Bruno Sciolla
  • Fabien Millioz
  • Marilys Almar
  • Philippe Delachartre
Original Article

Abstract

This paper addresses the detection of emboli in transcranial Doppler ultrasound data acquired from an original portable device. The challenge is the removal of several artifacts (motion and voice) intrinsically related to long-duration (up to 1 h 40 mn per patient) outpatient signals monitoring from this device, as well as high intensities due to the stochastic nature of blood flow. This paper proposes an adapted removal procedure. This firstly consists of reducing the background noise and detecting the blood flow in the time–frequency domain using a likelihood method for contour detection. Then, a hierarchical extraction of features from magnitude and bounding boxes is achieved for the discrimination of emboli and artifacts. After processing of the long-duration outpatient signals, the number of artifacts predicted as emboli is considerably reduced (by 92% for some parameter values) between the first and the last step of our algorithm.

Keywords

Emboli detection Transcranial Doppler Ultrasound Time–frequency approach Likelihood Spectral kurtosis Artifacts rejection 

Notes

Acknowledgements

This work was funded by the ANR-13-LAB3-0006-01 LabCom AtysCrea and was supported by the LABEX CELYA (ANR-10-LABX-0060) and PRIMES (ANR-11-LABX-0063) of Université de Lyon, within the program “Investissements d’Avenir” (ANR-11-IDEX-0007) operated by the French National Research Agency (ANR).

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Copyright information

© International Federation for Medical and Biological Engineering 2017

Authors and Affiliations

  • Blaise Kévin Guépié
    • 1
    Email author
  • Bruno Sciolla
    • 1
  • Fabien Millioz
    • 1
  • Marilys Almar
    • 2
  • Philippe Delachartre
    • 1
  1. 1.Univ Lyon, INSA-Lyon, Universit Claude Bernard Lyon 1, UJM-Saint Etienne, CNRS, Inserm,CREATIS UMR 5220, U1206LyonFrance
  2. 2.Atys MedicalSoucieu en JarrestFrance

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