Oil-immersion microscope objective lenses have been designed and optimized for the study of thin, two-dimensional object sections that are mounted immediately below the coverslip in a medium that is index matched to the immersion oil. It has been demonstrated both experimentally and through geometrical- and physical-optics theory that, when the microscope is not used with the correct coverslip or immersion oil, when the detector is not located at the optimal plane in image space, or when the object does not satisfy specific conditions, aberration will degrade both the contrast and the resolution of the image. In biology the most severe aberration is introduced when an oil-immersion objective lens is used to study thick specimens, such as living cells and tissues, whose refractive indices are significantly different from that of the immersion oil. We present a model of the three-dimensional imaging properties of a fluorescence light microscope subject to such aberration and compare the imaging properties predicted by the model with those measured experimentally. The model can be used to understand and compensate for aberration introduced to a microscope system under nondesign optical conditions so that both confocal laser scanning microscopy and optical serial sectioning microscopy can be optimized.
Existing formulations of the three-dimensional (3-D) diffraction pattern of spherical waves that is produced by a circular aperture are reviewed in the context of 3-D serial-sectioning microscopy. A new formulation for off-axis focal points is introduced that has the desirable properties of increased accuracy for larger field angles, invariance to shifts of the focal point about spheres of constant radius when the detection point is on the sphere for both intensity and amplitude fields, and invariance to shifts in three transformed coordinates for intensity fields. Finally, calculated intensity fields for both on-axis and off-axis focal points are included to illustrate the proposal that the classical 3-D diffraction patterns that have been used as analytical models in 3-D serial-sectioning fluorescence microscopy may not be accurate enough for this application.
This paper describes a method for creating object surfaces from binary-segmented data that are free from aliasing and terracing artifacts. In this method, a net of linked surface nodes is created over the surface of the binary object. The positions of the nodes are adjusted iteratively to reduce energy in the surface net while satisfying the constraint that each element in the surface net must remain within its original surface cube. This constraint ensures that fine detail such as cracks and thin protrusions that are present in the binary data are maintained.This work may not be copied or reproduced in whole or in part for any commercial purpose. Permission to copy in whole or in part without payment of fee is granted for nonprofit educational and research purposes provided that all such whole or partial copies include the following: a notice that such copying is by permission of Mitsubishi Electric Research Laboratories, Inc.; an acknowledgment of the authors and individual contributions to the work; and all applicable portions of the copyright notice. Copying, reproduction, or republishing for any other purpose shall require a license with payment of fee to Mitsubishi Electric Research Laboratories, Inc. All rights reserved. Abstract. This paper describes a method for creating object surfaces from binary-segmented data that are free from aliasing and terracing artifacts. In this method, a net of linked surface nodes is created over the surface of the binary object. The positions of the nodes are adjusted iteratively to reduce energy in the surface net while satisfying the constraint that each element in the surface net must remain within its original surface cube. This constraint ensures that ne detail such a s c r a c ks and thin protrusions that are present in the binary data are maintained.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.