Abstract
While deep learning has led to breakthroughs in many areas of computer science, its power has yet to be fully exploited in the area of adaptive optics (AO) and astronomy as a whole. In this paper we describe the first steps taken to apply deep, convolutional neural networks to the problem of wavefront reconstruction and prediction and demonstrate their feasibility of use in simulation. Our preliminary results show we are able to reconstruct wavefronts comparably well to current state of the art methods. We further demonstrate the ability to predict future wavefronts up to five simulation steps with under 1nm RMS wavefront error.

Abstract
The performance of an Adaptive Optics (AO) System relies on the accuracy of its Interaction Matrix which defines the opto-geometrical link between the Deformable Mirror (DM) and the Wave Front Sensor (WFS). Any mis-registrations (relative shifts, rotation, magnification or higher order pupil distortion) will strongly impact the performance, especially for high orders AO systems. Adaptive Telescopes provide a constraining environment for the AO calibration with large number of actuators DM, located inside the telescope with often no access to a calibration source and with a high accuracy required. The future Extremely Large Telescope (ELT) will take these constraints to another level with a longer calibration time required, no artificial calibration source and most of all, frequent updates of the calibration during the operation. To overcome these constraints, new calibration strategies have to be developed either doing it on-sky or working with synthetic models. The most promising approach seems to be the Pseudo-Synthetic Calibration. The principle is to generate the Interaction Matrix of the system in simulator, injecting the correct model alignment parameters identified from on-sky Measurements. It is currently the baseline for the Adaptive Optics Facility (AOF) at the Very Large Telescope (VLT) working with a Shack-Hartmann WFS but it remains to be investigated in the case of the Pyramid WFS.

Abstract
Geared by the increasing need for enhanced performance, both optical and computational, new dynamic control laws have been researched in recent years for next generation adaptive optics systems on current 10 m-class and extremely large telescopes up to 40 m. We provide an overview of these developments and point out prospects to making such controllers drive actual systems on-sky.

Abstract
Shack-Hartmann wavefront sensing relies on accurate spot centre measurement. Several algorithms were developed with this aim, mostly focused on precision, i.e. minimizing random errors. In the solar and extended scene community, the importance of the accuracy (bias error due to peak-locking, quantization, or sampling) of the centroid determination was identified and solutions proposed. But these solutions only allow partial bias corrections. To date, no systematic study of the bias error was conducted. This article bridges the gap by quantifying the bias error for different correlation peak-finding algorithms and types of sub-aperture images and by proposing a practical solution to minimize its effects. Four classes of sub-aperture images (point source, elongated laser guide star, crowded field, and solar extended scene) together with five types of peak-finding algorithms (1D parabola, the centre of gravity, Gaussian, 2D quadratic polynomial, and pyramid) are considered, in a variety of signal-to-noise conditions. The best performing peak-finding algorithm depends on the sub-aperture image type, but none is satisfactory to both bias and random errors. A practical solution is proposed that relies on the antisymmetric response of the bias to the sub-pixel position of the true centre. The solution decreases the bias by a factor of similar to 7 to values of less than or similar to 0.02 pix. The computational cost is typically twice of current cross-correlation algorithms.

Abstract
Knowledge of the optical properties of tissues is necessary, since they change from tissue to tissue and can differ between normal and pathological conditions. These properties are used in light transport models with various areas of application. In general, tissues have significantly high scattering coefficient when compared to the absorption coefficient and such difference usually increases with decreasing wavelength. The study of the wavelength dependence of the optical properties has been already made for several animal and human tissues, but extensive research is still needed in this field. Considering that most of the Biophotonics techniques used in research and clinical practice use visible to NIR light, we have estimated the optical properties of colorectal muscle (muscularis propria) between 400 and 1000 nm. The samples used were collected from patients undergoing resection surgery for colorectal carcinoma. The estimated scattering coefficient for colorectal muscle decreases exponentially with wavelength from 122 cm(-1) at 400 nm to 95 cm(-1) at 650 nm and to 91 cm(-1) at 1000 nm. The absorption coefficient shows a wavelength dependence according to the behavior seen for other tissues, since it decreases from 8 cm(-1) at 400 nm to 2.6 cm(-1) at 650 nm and to 1.3 cm(-1) at 1000 nm. The estimated optical properties differ from the ones that we have previously obtained for normal and pathological colorectal mucosa. The data obtained in this study covers an extended spectral range and it can be used for planning optical clearing treatments for some wavelengths of interest.

Abstract
To characterize the optical clearing treatments in human colorectal tissues and possibly to differentiate between treatments of normal and pathological tissues, we have used a simple indirect method derived from Mie scattering theory to estimate the kinetics of the reduced scattering coefficient. A complementary method to estimate the kinetics of the scattering coefficient is also used so that the kinetics of the anisotropy factor and of the refractive index are also calculated. Both methods rely only on the thickness and collimated transmittance measurements made during treatment. The results indicate the expected time dependencies for the optical properties of both tissues: an increase in the refractive index and anisotropy factor and a decrease in the scattering coefficients. The similarity in the kinetics obtained for normal and pathological tissues indicates that optical clearing treatments can be applied also in pathological tissues to produce similar effects. The estimated time dependencies using experimental spectral data in the range from 400 to 1000 nm allowed us to compare the kinetics of the optical properties between different wavelengths. (C) 2018 Society of Photo-Optical Instrumentation Engineers (SPIE)