Artificial intelligence in cancer imaging: Clinical challenges and applications

Wenya Linda Bi, Ahmed Hosny, Matthew B. Schabath, Maryellen L. Giger, Nicolai J. Birkbak, Alireza Mehrtash, Tavis Allison, Omar Arnaout, Christopher Abbosh, Ian F. Dunn, Raymond H. Mak, Rulla M. Tamimi, Clare M. Tempany, Charles Swanton, Udo Hoffmann, Lawrence H. Schwartz, Robert J. Gillies, Raymond Y. Huang, Hugo J. W. L. Aerts*

*Corresponding author for this work

Research output: Contribution to journalReview articleAcademicpeer-review

Original languageEnglish
Pages (from-to)127-157
Number of pages31
JournalCa-A Cancer Journal for Clinicians
Volume69
Issue number2
DOIs
Publication statusPublished - 2019

Keywords

  • artificial intelligence
  • cancer imaging
  • clinical challenges
  • deep learning
  • radiomics
  • COMPUTER-AIDED DETECTION
  • DIGITAL BREAST TOMOSYNTHESIS
  • BACKGROUND PARENCHYMAL ENHANCEMENT
  • CONVOLUTIONAL NEURAL-NETWORK
  • MULTI-PARAMETRIC MRI
  • DETECTION CAD SYSTEM
  • HIGH-GRADE GLIOMAS
  • PROSTATE-CANCER
  • LUNG-CANCER
  • PULMONARY NODULES

Cite this

Bi, W. L., Hosny, A., Schabath, M. B., Giger, M. L., Birkbak, N. J., Mehrtash, A., Allison, T., Arnaout, O., Abbosh, C., Dunn, I. F., Mak, R. H., Tamimi, R. M., Tempany, C. M., Swanton, C., Hoffmann, U., Schwartz, L. H., Gillies, R. J., Huang, R. Y., & Aerts, H. J. W. L. (2019). Artificial intelligence in cancer imaging: Clinical challenges and applications. Ca-A Cancer Journal for Clinicians, 69(2), 127-157. https://doi.org/10.3322/caac.21552