Speckle variance detection of microvasculature using swept-source optical coherence tomography.

By A. Mariampillai, B. Standish, E. Moriyama, M. Khurana, N. Munce, Michael K. K. Leung, James Y. Jiang, A. Cable, Brian C. Wilson, I. Vitkin and 1 more. Optics Letters, 2008

697 citations recorded by the source corpus.

Subfields: Biomedical Engineering, Ophthalmology

View Paper: https://www.semanticscholar.org/paper/5e58bc2ea1015d1c79925970767163d00febb278

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Biomedical Engineering

1. R. Spaide
2. Nadia K. Waheed
3. SriniVas R. Sadda
4. G. Staurenghi
5. James G. Fujimoto
6. Michael A. D. Taylor
7. Warwick P. Bowen

In Ophthalmology

1. Nadia K. Waheed
2. SriniVas R. Sadda
3. G. Staurenghi
4. James G. Fujimoto
5. R. Spaide
6. Yali Jia
7. Joachim Hornegger

Citations in the corpus

• Optical coherence tomography angiography (2017, methodology): “If other parameters are kept constant, longer interscan times increase sensitivity to motion because more time has elapsed between the repeated B-scans.”
• Split-spectrum amplitude-decorrelation angiography with optical coherence tomography (2012, methodology): “A technique termed “speckle variance” using swept-source OCT [32, 33] has demonstrated a significant improvement in capillary detection in tumors by calculation of the variance of the OCT signal intensity.”
• Optical Coherence Tomography Angiography (2016, methodology): “Mariampillai et al.36 extended the technique and presented speckle variance detection of microvasculature in a dorsal skinfold model using a swept-source OCT system in 2008.”