This Small Business Innovation Research Phase I project will apply emerging multispectral acousto-optic imaging technology and a specially devised unsupervised learning neural network to enhance microscopic imaging. Various spectral systems employing fluorescence, absorption, and Raman effect are currently in wide use in the microscopic investigation of biological structures. Physical Optics Corporation's R&D Division proposes to develop a novel spectrally adaptive system to enhance image quality and to improve the amount of light collected by an imaging camera as compared with single line filtering. At the same time, the signal-to-noise ratio will be drastically reduced since the system's spectral response will automatically be matched to the spectrum of the object of interest. The proposed system will also reduce the required observation time and the illumination of the sample under test, permitting real-time tracking of dynamic events in the sample without its being damaged by intensive illumination.

Agency
National Science Foundation (NSF)
Institute
Division of Industrial Innovation and Partnerships (IIP)
Type
Standard Grant (Standard)
Application #
9460580
Program Officer
G. Patrick Johnson
Project Start
Project End
Budget Start
1995-05-01
Budget End
1996-07-31
Support Year
Fiscal Year
1994
Total Cost
$74,972
Indirect Cost
Name
Physical Optics Corporation (Corporate Headquarters)
Department
Type
DUNS #
City
Torrance
State
CA
Country
United States
Zip Code
90501