Artificial Intelligence and Deep Learning of Head and Neck Cancer

Ahmed Abdel Khalek Abdel Razek; Reem Khaled; Eman Helmy; Ahmed Naglah; Amro AbdelKhalek; Ayman El-Baz

doi:10.1016/j.mric.2021.06.016

Artificial Intelligence and Deep Learning of Head and Neck Cancer

Magn Reson Imaging Clin N Am. 2022 Feb;30(1):81-94. doi: 10.1016/j.mric.2021.06.016.

Authors

Ahmed Abdel Khalek Abdel Razek¹, Reem Khaled², Eman Helmy², Ahmed Naglah³, Amro AbdelKhalek⁴, Ayman El-Baz³

Affiliations

¹ Department of Diagnostic Radiology, Mansoura University, Elgomheryia Street, Mansoura 35512, Egypt. Electronic address: arazek@mans.edu.eg.
² Department of Diagnostic Radiology, Mansoura University, Elgomheryia Street, Mansoura 35512, Egypt.
³ BioImaging Laboratory, Department of Bioengineering, University of Louisville, J.B. Speed School of Engineering, Lutz Hall, 200 E Shipp Avenue, Louisville, KY 40208, USA.
⁴ Internship at Mansoura University Hospital, Mansoura Faculty of Medicine, Elgomheryia Street, Mansoura 35512, Egypt.

PMID: 34802583
DOI: 10.1016/j.mric.2021.06.016

Abstract

Artificial intelligence (AI) algorithms, particularly deep learning, have developed to the point that they can be applied in image recognition tasks. The use of AI in medical imaging can guide radiologists to more accurate image interpretation and diagnosis in radiology. The software will provide data that we cannot extract from the images. The rapid development in computational capabilities supports the wide applications of AI in a range of cancers. Among those are its widespread applications in head and neck cancer.

Keywords: Artificial intelligence; Head and neck cancer; Radiomics; Texture analysis.

Publication types

Review

MeSH terms

Algorithms
Artificial Intelligence
Deep Learning*
Head and Neck Neoplasms* / diagnostic imaging
Humans
Magnetic Resonance Imaging