Search

Computational adaptive optics (CAO) is emerging as an attractive alternative to hardware-based solutions for diffraction-limited optical coherence tomography, e.g., of the human retina. Still, to become a reliable and robust solution, many challenges need to be solved. Here, we present CAO based on multiple randomized sub-apertures in combination with suitable filtering to remove disturbing artifacts. We show that this approach can reliably detect aberrations, and we compare results to other algorithms, such as optimization of imaging quality. We also demonstrate that the filtering of reflecting image structures is essential for a robust determination of aberrations.

Non-invasive functional retinal imaging in humans is of tremendous interest. By using phase-sensitive full-field swept-source OCT (FF-SS-OCT) we demonstrated simultaneous quantitative imaging of the optical activation in the photoreceptor and ganglion/inner plexiform layer. Since the signals from the ganglion cells layer are ten-fold smaller than those from the photoreceptor cells a new algorithms for suppression of motion artifacts and pulsatile blood flow in the retinal vessels is important. With improved data evaluation we simultaneously measured the activation of photoreceptors and ganglion/inner plexiform with high quality and were able to analyze the spatial and temporal response of cells in the ganglion/inner plexiform over more than 10 seconds.

Using phase-sensitive full-field swept-source optical coherence tomography we already showed that morphological changes in the photoreceptor outer segments are detectable. Those signals manifest themselves in an elongation of the optical path length. Using improved post.processing we report on progress in detecting signals in the neuronal layers of the human retina. The spatially resolved signals show a characteristic time course and by combining these with simultaneous measurements of the photoreceptors we were able to generate a wiring map of the neuronal retina.

Phase-sensitive coherent imaging exploits changes in the phases of backscattered light to observe tiny alterations of scattering structures or variations of the refractive index. But moving scatterers or a fluctuating refractive index decorrelate the phases and speckle patterns in the images. It is generally believed that once the speckle pattern has changed, the phases are scrambled and any meaningful phase difference to the original pattern is removed. As a consequence, diffusion and tissue motion below the resolution handicap phase-sensitive imaging of biological specimen. Here, we show that, surprisingly, a phase comparison between decorrelated speckle patterns is still possible by utilizing a series of images acquired during decorrelation. The resulting evaluation scheme is mathematically equivalent to methods for astronomic imaging through the turbulent sky by speckle interferometry. We thus adopt the idea of speckle interferometry to phase-sensitive imaging in biological tissues and demonstrate its efficacy for simulated data and for imaging of photoreceptor activity with phase-sensitive optical coherence tomography. The described methods can be applied to any imaging modality that uses phase values for interferometry., Comment: 13 pages, 5 figures

Functional retinal imaging, especially of neuronal activity non-invasively in humans, is of tremendous interest. Although the activation of photoreceptor cells (PRCs) could be detected in humans, imaging the function of other retinal neurons had been so far hardly possible. Here, using phase-sensitive full-field swept-source optical coherence tomography (FF-SS-OCT), we show simultaneous imaging of the activation in the photoreceptor and ganglion cell layer/inner plexiform layer (GCL/IPL). The signals from the GCL/IPL are 10-fold smaller than those from the PRC and were detectable only using algorithms for suppression of motion artifacts and pulsatile blood flow in the retinal vessels. FF-SS-OCT with improved phase evaluation algorithms, therefore, allowed us to map functional connections between PRC and GCL/IPL, confirming previous ex vivo results. The demonstrated functional imaging of retinal neuronal layers can be a valuable tool in diagnostics and basic research.

Computational adaptive optics (CAO) is emerging as a viable alternative to hardware-based adaptive optics-in particular when applied to optical coherence tomography of the retina. For this technique, algorithms are required that detect wavefront errors precisely and quickly. Here we propose an extension of the frequently used subaperture image correlation. By applying this algorithm iteratively and, more importantly, comparing each subaperture not to the central subaperture but to several randomly selected apertures, we improved aberration correction. Since these modifications only slightly increase the run time of the correction, we believe this method can become the algorithm of choice for many CAO applications.