%Aigaion2 BibTeX export from Idiap Publications
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@TECHREPORT{Shajkofci_Idiap-RR-07-2018,
                      author = {Shajkofci, Adrian and Liebling, Michael},
                    projects = {Idiap},
                       month = {6},
                       title = {Semi-blind spatially-variant deconvolution in optical microscopy with local Point Spread Function estimation by use of Convolutional Neural Networks},
                        type = {Idiap-RR},
                      number = {Idiap-RR-07-2018},
                        year = {2018},
                 institution = {Idiap},
                        note = {Accepted to IEEE ICIP 2018},
                    abstract = {We present a semi-blind, spatially-variant deconvolution technique aimed at optical microscopy that combines a local estimation step of the point spread function (PSF) and deconvolution using a spatially variant, regularized Richardson-Lucy algorithm. To find the local PSF map in a computationally tractable way, we train a convolutional neural network to perform regression of an optical parametric model on synthetically blurred image patches.
We deconvolved both synthetic and experimentally-acquired data, and achieved an improvement of image SNR of 1.00 dB on average, compared to other deconvolution algorithms.},
                         pdf = {https://publications.idiap.ch/attachments/reports/2018/Shajkofci_Idiap-RR-07-2018.pdf}
}