Comparison of wavelet transformations to enhance convolutional neural network performance in brain tumor segmentation.

Journal: BMC medical informatics and decision making
Published Date: Nov 23, 2021

Abstract

INTRODUCTION AND GOAL TO BACKGROUND: Due to the importance of segmentation of MRI images in identifying brain tumors, various methods including deep learning have been introduced for automatic brain tumor segmentation. On the other hand, using a combination of methods can improve their performance. Among them is the use of wavelet transform as an auxiliary element in deep networks. The analysis of the requirements of such combinations has been addressed in this study.

Authors

  • Mohamadreza Hajiabadi
    Brain and Spinal Cord Injury Research Center, Neuroscience Institute, and Iranian International Neuroscience Institute, Shariati Hospital, Tehran University of Medical Sciences, Tehran, Iran.
  • Behrouz Alizadeh Savareh
    PhD in Medical Informatics, National Agency for Strategic Research in Medical Education, Tehran, Iran; Department of health information management, school of management and medical information sciences, Shiraz University of Medical Sciences, Shiraz, Iran.
  • Hassan Emami
    Faculty of Allied Medical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
  • Azadeh Bashiri
    Department of health information management, school of management and medical information sciences, Shiraz University of Medical Sciences, Shiraz, Iran.

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