There has been increasing interest in recent years in techniques for microscopic examination of optically thick transparent objects. A number of phase imaging modalities have been developed to address this need. If a stack of images is acquired through focusing, the image at a given focal plane is contaminated by out-of-focus information coming from other planes [1]. There is a need to develop 3D imaging models for phase microscopes that will allow deconvolution, or more generally inverse reconstruction, techniques to be developed. Thus there is a need for an image formation model for phase microscopy that is able to maintain accuracy for thick objects but is more computationally tractable than full physical modeling. In response to this need we have developed a product of convolutions (POC) model. The need for the POC model arises because the Born approach fails with thick objects because the field of each object plane at the image plane is calculated by a superposition of all the fields from other object planes. As a consequence, since we are adding fields rather than phases, the phase introduced by light propagating through these planes is not well reconstructed at the image plane.


Poster presented at the 2007 Thrust R1B Effective Forward Models Conference


Microscopy Imaging, Model

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Three-dimensional imaging




Bernard M. Gordon Center for Subsurface Sensing and Imaging Systems (Gordon-CenSSIS)

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Bernard M. Gordon Center for Subsurface Sensing and Imaging Systems (Gordon-CenSSIS)

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