Deep learning approaches for automated classification and segmentation of head and neck cancers and brain tumors in magnetic resonance images: a meta-analysis study.

Journal: International journal of computer assisted radiology and surgery
Published Date: Mar 5, 2021

Abstract

PURPOSE: Deep learning (DL) has led to widespread changes in automated segmentation and classification for medical purposes. This study is an attempt to use statistical methods to analyze studies related to segmentation and classification of head and neck cancers (HNCs) and brain tumors in MRI images.

Authors

  • Samireh Badrigilan
    Department of Medical Physics, Kermanshah University of Medical Sciences, Kermanshah, Iran.
  • Shahabedin Nabavi
    Faculty of Computer Science and Engineering, Shahid Beheshti University, Tehran, Iran.
  • Ahmad Ali Abin
    Faculty of Computer Science and Engineering, Shahid Beheshti University, Tehran, Iran.
  • Nima Rostampour
    Department of Medical Physics, School of Medicine, Kermanshah University of Medical Sciences, Kermanshah, Iran. nima.rostampour@kums.ac.ir.
  • Iraj Abedi
    Department of Medical Physics, School of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran.
  • Atefeh Shirvani
    Department of Medical Physics, School of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran.
  • Mohsen Ebrahimi Moghaddam
    Faculty of Computer Science and Engineering, Shahid Beheshti University, Tehran, Iran.

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