POINT-SPREAD FUNCTION MODEL FOR FLUORESCENCE MACROSCOPY IMAGING - Inria - Institut national de recherche en sciences et technologies du numérique
Conference Papers Year : 2010

POINT-SPREAD FUNCTION MODEL FOR FLUORESCENCE MACROSCOPY IMAGING

Abstract

In this paper, we model the point-spread function (PSF) of a fluo- rescence MACROscope with a field aberration. The MACROscope is an imaging arrangement that is designed to directly study small and large specimen preparations without physically sectioning them. However, due to the different optical components of the MACRO- scope, it cannot achieve the condition of lateral spatial invariance for all magnifications. For example, under low zoom settings, this field aberration becomes prominent, the PSF varies in the lateral field, and is proportional to the distance from the center of the field. On the other hand, for larger zooms, these aberrations become gradually ab- sent. A computational approach to correct this aberration often relies on an accurate knowledge of the PSF. The PSF can be defined either theoretically using a scalar diffraction model or empirically by ac- quiring a three-dimensional image of a fluorescent bead that approx- imates a point source. The experimental PSF is difficult to obtain and can change with slight deviations from the physical conditions. In this paper, we model the PSF using the scalar diffraction approach, and the pupil function is modeled by chopping it. By comparing our modeled PSF with an experimentally obtained PSF, we validate our hypothesis that the spatial variance is caused by two limiting optical apertures brought together on different conjugate planes.
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Dates and versions

inria-00555940 , version 1 (14-01-2011)

Identifiers

  • HAL Id : inria-00555940 , version 1
  • PRODINRA : 246744
  • WOS : 000305886000254

Cite

Praveen Pankajakshan, Zvi Kam, Alain Dieterlen, Gilbert Engler, Laure Blanc-Féraud, et al.. POINT-SPREAD FUNCTION MODEL FOR FLUORESCENCE MACROSCOPY IMAGING. Forty-fourth asilomar conference on signals, systems and computers, IEEE Signal Processing Society, Nov 2010, Monterey, United States. ⟨inria-00555940⟩
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