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A Model-Based Approach to Extended Depth of Field for Brightfield Microscopy

F. Aguet, D. Van De Ville, M. Unser

Proceedings of the 2007 Annual Meeting of the Swiss Society of Biomedical Engineering (SSBE'07), Neuchâtel NE, Swiss Confederation, September 13-14, 2007, pp. 8.



Brightfield microscopy suffers from a limited depth of field, often preventing thick specimens from being imaged entirely in-focus. By optically sectioning the specimen, the in-focus regions can be acquired over multiple images. Extended depth of field methods aim at combining the information from these images into a single in-focus image of the texture on the specimen's surface. For the analysis of the in-focus image, knowledge of the specimen's topography can be mandatory. The topography provided by current methods is usually limited to a map of selected pixel positions and is inherently discretized, which limits its use for quantitative evaluation [1, 2]. In this work, we present a joint estimation of the in-focus image (texture) and the topography, based on a model of the specimen and the microscope's point spread function (PSF). The method, which can be likened to an object model-based deconvolution, produces a continuous topography.

References

  1. A.G. Valdecasas, D. Marshall, J.M. Becerra, J.J. Terrero, "On the Extended Depth of Focus Algorithms for Bright Field Microscopy," Micron, vol. 32, no. 6, pp. 559-569, August 2001.

  2. B. Forster, D. Van De Ville, J. Berent, D. Sage, M. Unser, "Complex Wavelets for Extended Depth-of-Field: A New Method for the Fusion of Multichannel Microscopy Images," Microscopy Research and Technique, vol. 65, no. 1-2, pp. 33-42, September 2004.

Max Anliker Memorial Poster Award


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