Wavefront sensorless adaptive optics OCT with the DONE algorithm for in vivo human retinal imaging [Invited]

In this report, which is an international collaboration of OCT, adaptive optics, and control research, we demonstrate the Data-based Online Nonlinear Extremum-seeker (DONE) algorithm to guide the image based optimization for wavefront sensorless adaptive optics (WFSL-AO) OCT for human retinal imagin...

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Published inBiomedical optics express Vol. 8; no. 4; pp. 2261 - 2275
Main Authors Verstraete, Hans R. G. W., Heisler, Morgan, Ju, Myeong Jin, Wahl, Daniel, Bliek, Laurens, Kalkman, Jeroen, Bonora, Stefano, Jian, Yifan, Verhaegen, Michel, Sarunic, Marinko V.
Format Journal Article
LanguageEnglish
Published United States Optical Society of America 01.04.2017
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ISSN2156-7085
2156-7085
DOI10.1364/BOE.8.002261

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Abstract In this report, which is an international collaboration of OCT, adaptive optics, and control research, we demonstrate the Data-based Online Nonlinear Extremum-seeker (DONE) algorithm to guide the image based optimization for wavefront sensorless adaptive optics (WFSL-AO) OCT for human retinal imaging. The ocular aberrations were corrected using a multi-actuator adaptive lens after linearization of the hysteresis in the piezoelectric actuators. The DONE algorithm succeeded in drastically improving image quality and the OCT signal intensity, up to a factor seven, while achieving a computational time of 1 ms per iteration, making it applicable for many high speed applications. We demonstrate the correction of five aberrations using 70 iterations of the DONE algorithm performed over 2.8 s of continuous volumetric OCT acquisition. Data acquired from an imaging phantom and from human research volunteers are presented.
AbstractList In this report, which is an international collaboration of OCT, adaptive optics, and control research, we demonstrate the Data-based Online Nonlinear Extremum-seeker (DONE) algorithm to guide the image based optimization for wavefront sensorless adaptive optics (WFSL-AO) OCT for in vivo human retinal imaging. The ocular aberrations were corrected using a multi-actuator adaptive lens after linearization of the hysteresis in the piezoelectric actuators. The DONE algorithm succeeded in drastically improving image quality and the OCT signal intensity, up to a factor seven, while achieving a computational time of 1 ms per iteration, making it applicable for many high speed applications. We demonstrate the correction of five aberrations using 70 iterations of the DONE algorithm performed over 2.8 s of continuous volumetric OCT acquisition. Data acquired from an imaging phantom and in vivo from human research volunteers are presented.
In this report, which is an international collaboration of OCT, adaptive optics, and control research, we demonstrate the Data-based Online Nonlinear Extremum-seeker (DONE) algorithm to guide the image based optimization for wavefront sensorless adaptive optics (WFSL-AO) OCT for human retinal imaging. The ocular aberrations were corrected using a multi-actuator adaptive lens after linearization of the hysteresis in the piezoelectric actuators. The DONE algorithm succeeded in drastically improving image quality and the OCT signal intensity, up to a factor seven, while achieving a computational time of 1 ms per iteration, making it applicable for many high speed applications. We demonstrate the correction of five aberrations using 70 iterations of the DONE algorithm performed over 2.8 s of continuous volumetric OCT acquisition. Data acquired from an imaging phantom and from human research volunteers are presented.
Author Kalkman, Jeroen
Verhaegen, Michel
Verstraete, Hans R. G. W.
Bliek, Laurens
Bonora, Stefano
Ju, Myeong Jin
Heisler, Morgan
Wahl, Daniel
Jian, Yifan
Sarunic, Marinko V.
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Snippet In this report, which is an international collaboration of OCT, adaptive optics, and control research, we demonstrate the Data-based Online Nonlinear...
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Title Wavefront sensorless adaptive optics OCT with the DONE algorithm for in vivo human retinal imaging [Invited]
URI https://www.ncbi.nlm.nih.gov/pubmed/28736670
https://pubmed.ncbi.nlm.nih.gov/PMC5516811
https://doi.org/10.1364/boe.8.002261
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