DocumentCode :
2806658
Title :
Image reconstruction of multiphoton microscopy data
Author :
Doot, Jared M. ; Eliceiri, Kevin W. ; Nowak, Robert D. ; Willett, Rebecca
Author_Institution :
Electr. & Comput. Eng., Univ. of Wisconsin-Madison, Madison, WI, USA
fYear :
2009
fDate :
June 28 2009-July 1 2009
Firstpage :
803
Lastpage :
806
Abstract :
The techniques introduced in this paper allow for accurate multiscale image reconstruction of multi-photon microscopy data. Multiphoton microscopy (MPM) is a tool for the non-invasive imaging of living organisms and tissue. The data acquired using this technique can contain information about the position, excited state lifetime, and spectra of the observed photons. The small number of photons collected, however, limits the quality of the reconstruction. The multiscale framework in this paper results in an accurate representation of both the intensity and excited state lifetime information. Using a multiscale reconstruction approach based on a penalized likelihood function, the underlying image is more accurately represented as compared to a naive aggregate binning approach.
Keywords :
biological tissues; biomedical optical imaging; image reconstruction; image representation; maximum likelihood estimation; medical image processing; multiphoton processes; optical microscopy; accurate image representation; biological tissue; excited state lifetime; image reconstruction; living organism; multiphoton microscopy data; noninvasive imaging; observed photon spectra; penalized likelihood function; Aggregates; Biomedical optical imaging; Data engineering; Fluorescence; Image reconstruction; Noise reduction; Optical imaging; Optical microscopy; Optical signal processing; Spatial resolution; Biomedical microscopy; Maximum likelihood estimation; Multidimensional signal processing; Poisson processes;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Biomedical Imaging: From Nano to Macro, 2009. ISBI '09. IEEE International Symposium on
Conference_Location :
Boston, MA
ISSN :
1945-7928
Print_ISBN :
978-1-4244-3931-7
Electronic_ISBN :
1945-7928
Type :
conf
DOI :
10.1109/ISBI.2009.5193171
Filename :
5193171
Link To Document :
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