Deep Learning in Biomedical Optics

Lei Tian; Brady Hunt; Muyinatu A Lediju Bell; Ji Yi; Jason T Smith; Marien Ochoa; Xavier Intes; Nicholas J Durr

doi:10.1002/lsm.23414

Deep Learning in Biomedical Optics

Lasers Surg Med. 2021 Aug;53(6):748-775. doi: 10.1002/lsm.23414. Epub 2021 May 20.

Authors

Lei Tian¹, Brady Hunt², Muyinatu A Lediju Bell^{3

4

5}, Ji Yi^{4

6}, Jason T Smith⁷, Marien Ochoa⁷, Xavier Intes⁷, Nicholas J Durr^{3

4}

Affiliations

¹ Department of Electrical and Computer Engineering, Boston University, 8 St. Mary's Street, RM 830, Boston, Massachusetts, 02215.
² Thayer School of Engineering, Dartmouth College, Hanover, New Hampshire, 03755.
³ Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, Maryland, 21218.
⁴ Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, 21218.
⁵ Department of Computer Science, Johns Hopkins University, Baltimore, Maryland, 21218.
⁶ Department of Ophthalmology, Johns Hopkins University, Baltimore, Maryland, 21287.
⁷ Center for Modeling, Simulation, and Imaging in Medicine, Rensselaer Polytechnic Institute, Troy, New York, 12180.

Abstract

This article reviews deep learning applications in biomedical optics with a particular emphasis on image formation. The review is organized by imaging domains within biomedical optics and includes microscopy, fluorescence lifetime imaging, in vivo microscopy, widefield endoscopy, optical coherence tomography, photoacoustic imaging, diffuse tomography, and functional optical brain imaging. For each of these domains, we summarize how deep learning has been applied and highlight methods by which deep learning can enable new capabilities for optics in medicine. Challenges and opportunities to improve translation and adoption of deep learning in biomedical optics are also summarized. Lasers Surg. Med. © 2021 Wiley Periodicals LLC.

Keywords: biomedical optics; biophotonics; computer aided detection; deep learning; diffuse tomography; fluorescence lifetime; functional optical brain imaging; in vivo microscopy; machine learning; microscopy; optical coherence tomography; photoacoustic imaging; widefield endoscopy.

Publication types

Research Support, N.I.H., Extramural
Research Support, U.S. Gov't, Non-P.H.S.
Review

MeSH terms

Deep Learning*
Microscopy
Optical Imaging
Optics and Photonics
Tomography, Optical Coherence

Abstract

Publication types

MeSH terms

Grants and funding