  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.
