TY  - GEN
UR  - https://archiv.ub.uni-heidelberg.de/volltextserver/6944/
N2  - In-vivo imaging of the eye's fundus is the basis for  the diagnosis of retinal diseases in ophthalmology.  However, the resolution of the images is limited -  besides the inevitable diffractive limitation by the  finite size of the pupil - by the imperfect optical  elements of the eye, causing aberrations. In astronomy,  first test measurements of atmospheric aberrations with  the novel 4-sided pyramid sensor have confirmed the  benefits of this sensor compared with conventional  wavefront sensors. This work presents a pyramid  wavefront sensor for the measurement of aberrations and  their compensation on a confocal laser scanning  ophthalmoscope. By contrast, a 3-sided pyramid prism is  used and it is demonstrated experimentally, that this  prism, which is easier to manufacture than the 4-sided  prism, reveals to be an equivalent sensor.  The control of the deformable mirror which can  compensate the aberrations is implemented by an  artificial neural network based on the acquired sensor  data. With the trained neural network, aberrations of  150nm RMS could already be reduced to half the error.  The neural network is composed of a convolutional  S_C-net of 2x4 layers, which extracts feature  information out of the signal images of the pyramid,  and a 3-layer, feed-forward backpropagation net, that  determines the required deflection of the mirror in  order to compensate for a given aberration.
A1  - Alvarez Diez, Cristina
AV  - public
ID  - heidok6944
KW  - Pyramiden Sensor 
KW  -  Wellenfrontsensor 
KW  -  Neuronales Netz 
KW  -  Bildaufnahmen der NetzhautPyramid sensor 
KW  -  wavefront sensor 
KW  -  neuronal network 
KW  -  retina imaging
Y1  - 2006///
TI  - A 3-sided Pyramid Wavefront Sensor Controlled by a Neural Network for Adaptive Optics to reach diffraction-limited Imaging of the Retina
ER  -