
Proceedings Paper
Digital filter based on the Fisher linear discriminant to reduce dead-time paralysis in photon countingFormat | Member Price | Non-Member Price |
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Paper Abstract
Photon counting represents the Poisson limit in signal to noise, but can often be complicated in imaging
applications by detector paralysis, arising from the finite rise / fall time of the detector upon photon absorption.
We present here an approach for reducing dead-time by generating a deconvolution digital filter based on
optimizing the Fisher linear discriminant. In brief, two classes are defined, one in which a photon event is
initiated at the origin of the digital filter, and one in the photon event is non-coincident with the filter origin.
Linear discriminant analysis (LDA) is then performed to optimize the digital filter that best resolves the
coincident and non-coincident training set data.1 Once trained, implementation of the filter can be performed
quickly, significantly reducing dead-time issues and measurement bias in photon counting applications.
Experimental demonstration of the LDA-filter approach was performed in fluorescence microscopy
measurements using a highly convolved impulse response with considerable ringing. Analysis of the counts
supports the capabilities of the filter in recovering deconvolved impulse responses under the conditions
considered in the study. Potential additional applications and possible limitations are also considered.
Paper Details
Date Published: 7 March 2014
PDF: 8 pages
Proc. SPIE 9020, Computational Imaging XII, 902009 (7 March 2014); doi: 10.1117/12.2048875
Published in SPIE Proceedings Vol. 9020:
Computational Imaging XII
Charles A. Bouman; Ken D. Sauer, Editor(s)
PDF: 8 pages
Proc. SPIE 9020, Computational Imaging XII, 902009 (7 March 2014); doi: 10.1117/12.2048875
Show Author Affiliations
Shane Z. Sullivan, Purdue Univ. (United States)
Paul D. Schmitt, Purdue Univ. (United States)
Emma L. DeWalt, Purdue Univ. (United States)
Paul D. Schmitt, Purdue Univ. (United States)
Emma L. DeWalt, Purdue Univ. (United States)
Published in SPIE Proceedings Vol. 9020:
Computational Imaging XII
Charles A. Bouman; Ken D. Sauer, Editor(s)
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