In vivo blind-deconvolution photoacoustic ophthalmoscopy with total variation regularization

Deyan Xie, Qin Li, Quanxue Gao*, Wei Song, Hao F. Zhang, Xiaocong Yuan

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

8 Scopus citations


Photoacoustic ophthalmoscopy (PAOM) is capable of noninvasively imaging anatomic and functional information of the retina in living rodents. However, the strong ocular aberration in rodent eyes and limited ultrasonic detection sensitivity affect PAOM's spatial resolution and signal-to-noise ratio (SNR) in in vivo eyes. In this work, we report a computational approach to combine blind deconvolution (BD) algorithm with a regularizing constraint based on total variation (BDTV) for PAOM imaging restoration. We tested the algorithm in retinal and choroidal microvascular images in albino rat eyes. The algorithm improved PAOM's lateral resolution by around 2-fold. Moreover, it enabled the improvement in imaging SNR for both major vessels and capillaries, and realized the well-preserved blood vessels' edges simultaneously, which surpasses conventional Richardson-Lucy BD algorithm. The reported results indicate that the BDTV algorithm potentially facilitate PAOM in extracting retinal pathophysiological information by enhancing in vivo imaging quality without physically modifying PAOM's optical configuration.

Original languageEnglish (US)
Article numbere201700360
JournalJournal of Biophotonics
Issue number9
StatePublished - Sep 2018


  • blind deconvolution
  • chorioretinal imaging
  • photoacoustic ophthalmoscopy
  • total variation

ASJC Scopus subject areas

  • Chemistry(all)
  • Materials Science(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Engineering(all)
  • Physics and Astronomy(all)


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