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1.
Opt Express ; 16(22): 18406-16, 2008 Oct 27.
Article in English | MEDLINE | ID: mdl-18958119

ABSTRACT

The phase diversity technique is a useful tool to measure and pre-compensate for quasi-static aberrations, in particular non-common path aberrations, in an adaptive optics corrected imaging system. In this paper, we propose and validate by simulations an extension of the phase diversity technique that uses long exposure adaptive optics corrected images for sensing quasi-static aberrations during the scientific observation, in particular for high-contrast imaging. The principle of the method is that, for a sufficiently long exposure time, the residual turbulence is averaged into a convolutive component of the image and that phase diversity estimates the sole static aberrations of interest. The advantages of such a procedure, compared to the processing of shortexposure image pairs, are that the separation between static aberrations and turbulence-induced ones is performed by the long-exposure itself and not numerically, that only one image pair must be processed, that the estimation benefits from the high SNR of long-exposure images, and that only the static aberrations of interest are to be estimated. Long-exposure phase diversity can also be used as a phasing sensor for a segmented aperture telescope. Thus, it may be particularly useful for future planet finder projects such as EPICS on the European ELT.

2.
J Clin Pathol ; 35(10): 1057-62, 1982 Oct.
Article in English | MEDLINE | ID: mdl-6290541

ABSTRACT

Liver cells from 20 normal livers and 20 hepatomas have been studied in histological sections using an interactive computer method which measures nuclear size and shape. The variables which gave best discrimination between malignant and benign nuclei were the standard deviations of nuclear shape measurements. Though the liver is an ideal tissue for computer study it is considered that such measurements may act as a model for analysis of nuclei of other tissues.


Subject(s)
Carcinoma, Hepatocellular/ultrastructure , Liver Neoplasms/ultrastructure , Liver/ultrastructure , Cell Nucleus/ultrastructure , Computers , Humans
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