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Flow Convergence Area Estimation on In Vitro Color Flow Doppler Images Using Deep Learning

  • Grigorios-Aris CheimariotisEmail author
  • Kostas Haris
  • Jeesoo Lee
  • Brent E. White
  • Aggelos K. Katsaggelos
  • James D. Thomas
  • Nikolaos Maglaveras
Conference paper
Part of the IFMBE Proceedings book series (IFMBE, volume 76)

Abstract

We present an automatic method to estimate flow rate through the orifice in in-vitro 2D color-flow Doppler echocardiographic images. Flow rate properties are important for the assessment of pathologies like mitral regurgitation. We expect this method to be transferable to in-vivo patient data. The method consists of two main parts: (a) detecting a bounding box which encloses aliasing contours and its surroundings (namely a region representative of flow convergence area), (b) application of Convolutional Neural Networks for regression to estimate the flow convergence area. Best result achieved is the 5% mean error for validation data which is from other experiments that were used for training. Given the small number of training data, this method shows promising results.

Keywords

Deep learning Color flow doppler Flow rate Mitral regurgitation 

Notes

Funding Sources

This research is funded by the Greek State Scholarships Foundation and European Social Fund.

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Grigorios-Aris Cheimariotis
    • 1
    Email author
  • Kostas Haris
    • 1
  • Jeesoo Lee
    • 2
  • Brent E. White
    • 2
  • Aggelos K. Katsaggelos
    • 3
  • James D. Thomas
    • 2
  • Nikolaos Maglaveras
    • 1
    • 2
    • 3
    • 4
  1. 1.Lab of Computing, Medical Informatics and Biomedical Imaging TechnologiesAristotle UniversityThessalonikiGreece
  2. 2.Department of Radiology, Feinberg School of MedicineNorthwestern UniversityChicagoUSA
  3. 3.Department of Electrical and Computer EngineeringNorthwestern UniversityEvanston, ChicagoUSA
  4. 4.Department of Industrial Engineering and Applied ScienceNorthwestern UniversityEvanston, ChicagoUSA

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