State-of-the-art review on deep learning in medical imaging.

Journal: Frontiers in bioscience (Landmark edition)
Published Date:

Abstract

Deep learning (DL) is affecting each and every sphere of public and private lives and becoming a tool for daily use. The power of DL lies in the fact that it tries to imitate the activities of neurons in the neocortex of human brain where the thought process takes place. Therefore, like the brain, it tries to learn and recognize patterns in the form of digital images. This power is built on the depth of many layers of computing neurons backed by high power processors and graphics processing units (GPUs) easily available today. In the current scenario, we have provided detailed survey of various types of DL systems available today, and specifically, we have concentrated our efforts on current applications of DL in medical imaging. We have also focused our efforts on explaining the readers the rapid transition of technology from machine learning to DL and have tried our best in reasoning this paradigm shift. Further, a detailed analysis of complexities involved in this shift and possible benefits accrued by the users and developers.

Authors

  • Mainak Biswas
    Department of Computer Science and Engineering, NIT, Goa, India.
  • Venkatanareshbabu Kuppili
    Department of Computer Science and Engineering, NIT, Goa, India.
  • Luca Saba
    Department of Radiology, A.O.U., Italy.
  • Damodar Reddy Edla
    Department of Computer Science and Engineering, NIT, Goa, India.
  • Harman S Suri
    Brown University, Providence, RI, USA; Monitoring and Diagnostic Division, AtheroPointâ„¢, Roseville, CA, USA.
  • Elisa Cuadrado-Godia
    IMIM-Hospital del Mar, Barcelona, Spain.
  • John R Laird
    UC Davis Vascular Center, University of California, Davis, CA, USA.
  • Rui Tato Marinhoe
    Liver Unit, Department of Gastroenterology and Hepatology, Hospital de Santa Maria, Medical School of Lisbon, Lisbon 1629-049, Portugal.
  • Joao M Sanches
    ISR, Instituto Superior Tecnico (IST), Lisboa, Portugal.
  • 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.