Benjamin J. Vakoc, Ph.D.
Affiliations: | 2001 | Stanford University, Palo Alto, CA |
Area:
Optics Physics, Electronics and Electrical EngineeringGoogle:
"Benjamin Vakoc"Mean distance: 13.4 | S | N | B | C | P |
Parents
Sign in to add mentor| Gordon S. Kino | grad student | 2001 | Stanford | |
| (Development of a novel Sagnac interferometer-based fiber-optic acoustic sensor array.) | ||||
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Publications
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| Harper DJ, Kim Y, Gómez-Ramírez A, et al. (2023) Needle guidance with Doppler-tracked polarization-sensitive optical coherence tomography. Journal of Biomedical Optics. 28: 102910 |
| Harper DJ, Kim Y, Gómez-Ramírez A, et al. (2023) Needle guidance with Doppler-tracked polarization-sensitive optical coherence tomography. Arxiv |
| Wong KKY, Wei X, Ji N, et al. (2023) Feature issue introduction: ultrafast optical imaging. Optics Express. 31: 8201-8204 |
| Saytashev I, Yoon YC, Vakoc BJ, et al. (2023) Improved optical coherence tomography imaging of animal peripheral nerves using a prism nerve holder. Journal of Biomedical Optics. 28: 026002 |
| Lee B, Jeong S, Lee J, et al. (2023) Wide-Field Three-Dimensional Depth-Invariant Cellular-Resolution Imaging of the Human Retina. Small (Weinheim An Der Bergstrasse, Germany). e2203357 |
| Harper DJ, Vakoc BJ. (2022) Relationship between axial resolution and signal-to-noise ratio in optical coherence tomography. Optics Letters. 47: 1517-1520 |
| Kim TS, Vakoc BJ. (2020) Stepped frequency comb generation based on electro-optic phase-code mode-locking for moderate-speed circular-ranging OCT. Biomedical Optics Express. 11: 3534-3542 |
| Park EA, Tsikata E, Lee JJ, et al. (2020) Artifact Rates for 2D Retinal Nerve Fiber Layer Thickness Versus 3D Neuroretinal Rim Thickness Using Spectral-Domain Optical Coherence Tomography. Translational Vision Science & Technology. 9: 10 |
| Choi S, Jassim F, Tsikata E, et al. (2020) Artifact Rates for 2D Retinal Nerve Fiber Layer Thickness Versus 3D Retinal Nerve Fiber Layer Volume. Translational Vision Science & Technology. 9: 12 |
| Braaf B, Donner S, Uribe-Patarroyo N, et al. (2020) A Neural Network Approach to Quantify Blood Flow from Retinal OCT Intensity Time-Series Measurements. Scientific Reports. 10: 9611 |