scholarly journals Semi-Blind Spatially-Variant Deconvolution in Optical Microscopy with Local Point Spread Function Estimation by Use of Convolutional Neural Networks

Author(s):  
Adrian Shajkofci ◽  
Michael Liebling
2021 ◽  
Vol 2086 (1) ◽  
pp. 012148
Author(s):  
P A Khorin ◽  
A P Dzyuba ◽  
P G Serafimovich ◽  
S N Khonina

Abstract Recognition of the types of aberrations corresponding to individual Zernike functions were carried out from the pattern of the intensity of the point spread function (PSF) outside the focal plane using convolutional neural networks. The PSF intensity patterns outside the focal plane are more informative in comparison with the focal plane even for small values/magnitudes of aberrations. The mean prediction errors of the neural network for each type of aberration were obtained for a set of 8 Zernike functions from a dataset of 2 thousand pictures of out-of-focal PSFs. As a result of training, for the considered types of aberrations, the obtained averaged absolute errors do not exceed 0.0053, which corresponds to an almost threefold decrease in the error in comparison with the same result for focal PSFs.


2011 ◽  
Vol 96 (2) ◽  
pp. 175-194 ◽  
Author(s):  
Mauricio Delbracio ◽  
Pablo Musé ◽  
Andrés Almansa ◽  
Jean-Michel Morel

2012 ◽  
Vol 2 ◽  
pp. 8-21 ◽  
Author(s):  
Mauricio Delbracio ◽  
Pablo Musé ◽  
Andrés Almansa

2013 ◽  
Vol 56 (12) ◽  
pp. 2701-2710 ◽  
Author(s):  
Raymond Honfu Chan ◽  
XiaoMing Yuan ◽  
WenXing Zhang

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