TY - JOUR
T1 - Combined hardware and computational optical wavefront correction
AU - South, Fredrick A.
AU - Kurokawa, Kazuhiro
AU - Liu, Zhuolin
AU - Liu, Yuan Zhi
AU - Miller, Donald T.
AU - Boppart, Stephen A.
N1 - Research reported in this publication was supported by the National Institute for Biomedical Imaging and Bioengineering; the National Cancer Institute; and the National Eye Institute of the National Institutes of Health under award number R01EB023232, R01EB13723, R01CA213149, R01EY018339, P30EY019008 respectively and Air Force Office of Scientific Research under award number FA9550-17-1-0387. One hundred percent of the total project costs were financed with Federal money and zero percent of the total costs were financed by nongovernmental sources. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
National Institutes of Health (NIH) (R01-CA213149, R01-EB013723, R01-EB023232, RO1-EY018339, P30-EY019008);Air Force Office of Scientific Research (FA9550-17-1-0387).
PY - 2018/6/1
Y1 - 2018/6/1
N2 - In many optical imaging applications, it is necessary to overcome aberrations to obtain high-resolution images. Aberration correction can be performed by either physically modifying the optical wavefront using hardware components, or by modifying the wavefront during image reconstruction using computational imaging. Here we address a longstanding issue in computational imaging: photons that are not collected cannot be corrected. This severely restricts the applications of computational wavefront correction. Additionally, performance limitations of hardware wavefront correction leave many aberrations uncorrected. We combine hardware and computational correction to address the shortcomings of each method. Coherent optical backscattering data is collected using high-speed optical coherence tomography, with aberrations corrected at the time of acquisition using a wavefront sensor and deformable mirror to maximize photon collection. Remaining aberrations are corrected by digitally modifying the coherently-measured wavefront during imaging reconstruction. This strategy obtains high-resolution images with improved signal-to-noise ratio of in vivo human photoreceptor cells with more complete correction of ocular aberrations, and increased flexibility to image at multiple retinal depths, field locations, and time points. While our approach is not restricted to retinal imaging, this application is one of the most challenging for computational imaging due to the large aberrations of the dilated pupil, time-varying aberrations, and unavoidable eye motion. In contrast with previous computational imaging work, we have imaged single photoreceptors and their waveguide modes in fully dilated eyes with a single acquisition. Combined hardware and computational wavefront correction improves the image sharpness of existing adaptive optics systems, and broadens the potential applications of computational imaging methods.
AB - In many optical imaging applications, it is necessary to overcome aberrations to obtain high-resolution images. Aberration correction can be performed by either physically modifying the optical wavefront using hardware components, or by modifying the wavefront during image reconstruction using computational imaging. Here we address a longstanding issue in computational imaging: photons that are not collected cannot be corrected. This severely restricts the applications of computational wavefront correction. Additionally, performance limitations of hardware wavefront correction leave many aberrations uncorrected. We combine hardware and computational correction to address the shortcomings of each method. Coherent optical backscattering data is collected using high-speed optical coherence tomography, with aberrations corrected at the time of acquisition using a wavefront sensor and deformable mirror to maximize photon collection. Remaining aberrations are corrected by digitally modifying the coherently-measured wavefront during imaging reconstruction. This strategy obtains high-resolution images with improved signal-to-noise ratio of in vivo human photoreceptor cells with more complete correction of ocular aberrations, and increased flexibility to image at multiple retinal depths, field locations, and time points. While our approach is not restricted to retinal imaging, this application is one of the most challenging for computational imaging due to the large aberrations of the dilated pupil, time-varying aberrations, and unavoidable eye motion. In contrast with previous computational imaging work, we have imaged single photoreceptors and their waveguide modes in fully dilated eyes with a single acquisition. Combined hardware and computational wavefront correction improves the image sharpness of existing adaptive optics systems, and broadens the potential applications of computational imaging methods.
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U2 - 10.1364/BOE.9.002562
DO - 10.1364/BOE.9.002562
M3 - Article
C2 - 30258673
AN - SCOPUS:85048149802
SN - 2156-7085
VL - 9
SP - 2562
EP - 2574
JO - Biomedical Optics Express
JF - Biomedical Optics Express
IS - 6
M1 - #322898
ER -