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27 April 2016 Learning from examples in optical tomography (Conference Presentation)
Demetri Psaltis
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Proceedings Volume 9718, Quantitative Phase Imaging II; 97181Z (2016) https://doi.org/10.1117/12.2212785
Event: SPIE BiOS, 2016, San Francisco, California, United States
Abstract
An optical tomography system measures the light scattered by an object as a function of spatial coordinates and as a function of the illumination angle. The measured signals are digitally processed to produce a 3D image of the object. In this paper we describe how we can learn the shape of an object by constructing a neural network that models the optical system and training the network to match the experimentally measured data. The variables of the trained network yield the image of the unknown object at the end of training phase. [1] Ulugbek, Papadopoulos, Shoreh, Goy, Vonesh, Unser, Psaltis, “A Learning Approach to Optical Tomography” Optica, May 2015.
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Demetri Psaltis "Learning from examples in optical tomography (Conference Presentation)", Proc. SPIE 9718, Quantitative Phase Imaging II, 97181Z (27 April 2016); https://doi.org/10.1117/12.2212785
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KEYWORDS
Optical tomography
Signal processing
3D image processing
Data modeling
Digital signal processing
Image processing
Light scattering
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