| Literature DB >> 34015146 |
Lei Tian1, Brady Hunt2, Muyinatu A Lediju Bell3,4,5, Ji Yi4,6, Jason T Smith7, Marien Ochoa7, Xavier Intes7, Nicholas J Durr3,4.
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.Entities:
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
Mesh:
Year: 2021 PMID: 34015146 PMCID: PMC8273152 DOI: 10.1002/lsm.23414
Source DB: PubMed Journal: Lasers Surg Med ISSN: 0196-8092