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Overview: Adaptive optics (AO) techniques allow to measure and manipulate the wavefront aberrations in real time. In 1997, reseachers in Institute of Optics and Electronics (IOE) took the lead in developing of adaptive optics technology in China. This article firstly introduces the principle of ocular adaptive optical system briefly, and then reports the main research progress of IOE for the last five years. In 2012, we measured the effects of perceptual learning on visual sensitivity with and without HOAs-correction both for normal adults, and older child and adult anisometropic amblyopes. We found larger and more robust contrast sensitivity improvements when the HOAs were corrected than when they were left uncorrected. In 2014, we investigated the effects of ocular aberrations on the binocular vision functions. Results showed that ocular aberrations had an inequable effect on the different binocular vision functions. In 2016, an adaptive optics double pass (DP) system was designed and developed for ocular scatter estimation. The experimental results showed that this system could improve the accuracy of ocular scatter estimation. Then we investigated the effect of HOAs and intraocular scatter on contrast sensitivity. Quantitative analysis suggested a potential compensatory mechanism between HOAs and intraocular scatter on contrast sensitivity. In 2016, an AO pattern reversal visual evoked potential (PR-VEP) measurement system was established. PR-VEP measurements were performed with HOAs either retained or corrected. The results confirmed the contributions of the HOAs to the alterations in PR-VEP, and suggested that HOAs should be corrected to realize accurate PR-VEP testing. In 2017, we proposed a deep learning method to restore the degraded retinal images. The method directly learned an end-to-end mapping between the blurred and restored retinal images. The mapping was represented as a deep convolutional neural network. This network was validated on synthetically generated retinal images as well as real AO retinal images. The assessment of the restored retinal images demonstrated that the image quality had been significantly improved.
Schematic diagram of a typical adaptive optical system for human eye[3]
Schematic diagram of adaptive optical perceptual learning system
(a1)~(d1) Contrast sensitivity function and its benefit for normal adults pre-and post-training with and without correction of high-order aberrations (HOAs). (a1) Average results trained under the HOAs-corrected condition[8]; (b1) Average post-and pre-training CSFs without HOAs-corrected; (c1) Average improvements of contrast sensitivity with and without HOAs-corrected; (d1) Average magnitude of contrast sensitivity improvements across observers and spatial frequencies. (a2)~(d2) Improvements in the CSF after perceptual learning for older children and adults with anisometropic amblyopia. (a2) Pre-and post-training CSFs for amblyopic eyes with AO correction[9]; (b2) Average improvements in CSF with AO correction (dB) as a function of pre-training amblyopic VA (logMAR); (c2) The learning effect with AO correction is maintained under the condition without AO correction for the amblyopic eyes; (d2) The learning effect with AO correction is transferred to the untrained fellow eyes
Schematic of binocular adaptive optical visual simulation system[10]
(a1)~(c1) Stereoacuity versus viewing duration under different optical conditions for the three subjects[11]. Blue squares represent stereoacuity with baseline correction, green circles and red triangles represent stereoacuity with binocular and better eye correction. (a2)~(d2) Stereo threshold versus exposure duration under different optical conditions for the 4 subjects on linear scales[12]. The blue squares represent stereoacuity with basic correction of defocus and astigmatism, the green circles and red triangles represent stereoacuity with binocular and better eye correction
Schematic diagram of the adaptive optics double pass PSF measurement system[21]
(a) The typical DP PSF images measured at the fovea for the left eyes of subjects in AO-DPPMS system with different aberration correction strategies[23]. First row, DP images with defocus and astigmatism corrected in the AO-DPPMS system; second row, DP images with aberrations corrected up to the 5th Zernike order with AO-DPPMS system; third row, DP images with aberrations corrected up to the 8th Zernike order with AO-DPPMS system; (b) Linear fit of impact factorHS (QHS) versus the sum of impact factorHOAs (QHOAS) and impact factorScatter (QScatter). Each point represent an average value across subjects for a spatial frequency. Blue circles stand for results obtained with filter S0.5; green triangles stand for results obtained with filter S1; magenta diamonds stand for results obtained with filter S2. The solid line represent the fitting line; the dotted line stand for the line y = x
AO system integrated visual performance evaluation with pattern reversal VEP measurements
Average VEP magnitude with low-order aberrations corrected and with high-order aberrations corrected
Network structure. A blurred image goes through layers and transforms into a restored one, we use 64 filters for each convolutional layer and some sample feature maps are drawn for visualization
Deconvolution results of a retinal image captured by AOSLO system. (a) Original image (0.9 mm eccentricity from the foveal center); (b) Restored by the proposed method; (c) Restored by the ALM method; (d) The corresponding normalized image power spectra, the scale bar is 50 µm