Deep learning strategy for accurate carotid intima-media thickness measurement: An ultrasound study on Japanese diabetic cohort.

Journal: Computers in biology and medicine
PMID: 29778925

Abstract

MOTIVATION: The carotid intima-media thickness (cIMT) is an important biomarker for cardiovascular diseases and stroke monitoring. This study presents an intelligence-based, novel, robust, and clinically-strong strategy that uses a combination of deep-learning (DL) and machine-learning (ML) paradigms.

Authors

  • Mainak Biswas
    Department of Computer Science and Engineering, NIT, Goa, India.
  • Venkatanareshbabu Kuppili
    Department of Computer Science and Engineering, NIT, Goa, India.
  • Tadashi Araki
    Division of Cardiovascular Medicine, Toho University Ohashi Medical Center, Tokyo, Japan.
  • Damodar Reddy Edla
    Department of Computer Science and Engineering, NIT, Goa, India.
  • Elisa Cuadrado Godia
    IMIM - Hospital del Mar, Passeig Marítim 25-29, Barcelona, Spain.
  • Luca Saba
    Department of Radiology, A.O.U., Italy.
  • Harman S Suri
    Brown University, Providence, RI, USA; Monitoring and Diagnostic Division, AtheroPoint™, Roseville, CA, USA.
  • Tomaž Omerzu
    Department of Neurology, University Medical Centre Maribor, Slovenia.
  • John R Laird
    UC Davis Vascular Center, University of California, Davis, CA, USA.
  • Narendra N Khanna
    Cardiology Department, Apollo Hospitals, New Delhi, India.
  • Andrew Nicolaides
    Vascular Screening and Diagnostic Centre, London, England, United Kingdom; Vascular Diagnostic Center, University of Cyprus, Nicosia, Cyprus.
  • Jasjit S Suri
    Advanced Knowledge Engineering Center, Global Biomedical Technologies, Inc., Roseville, CA, USA. Electronic address: jsuri@comcast.net.

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