A review of deep learning in medical imaging: Imaging traits, technology trends, case studies with progress highlights, and future promises.

MLA

Zhou, S.Kevin, et al. “A Review of Deep Learning in Medical Imaging: Imaging Traits, Technology Trends, Case Studies with Progress Highlights, and Future Promises.” Proceedings of the IEEE. Institute of Electrical and Electronics Engineers, vol. 109, no. 5, May 2021, pp. 820–38. EBSCOhost, https://doi.org/10.1109/JPROC.2021.3054390.

APA

Zhou, S. K., Greenspan, H., Davatzikos, C., Duncan, J. S., van Ginneken, B., Madabhushi, A., Prince, J. L., Rueckert, D., & Summers, R. M. (2021). A review of deep learning in medical imaging: Imaging traits, technology trends, case studies with progress highlights, and future promises. Proceedings of the IEEE. Institute of Electrical and Electronics Engineers, 109(5), 820–838. https://doi.org/10.1109/JPROC.2021.3054390

Chicago

Zhou, S Kevin, Hayit Greenspan, Christos Davatzikos, James S Duncan, Bram van Ginneken, Anant Madabhushi, Jerry L Prince, Daniel Rueckert, and Ronald M Summers. 2021. “A Review of Deep Learning in Medical Imaging: Imaging Traits, Technology Trends, Case Studies with Progress Highlights, and Future Promises.” Proceedings of the IEEE. Institute of Electrical and Electronics Engineers 109 (5): 820–38. doi:10.1109/JPROC.2021.3054390.