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Proceedings Paper

Automatic identification of bacterial types using statistical imaging methods
Author(s): Sigal Trattner; Hayit Greenspan; Gapi Tepper; Shimon Abboud
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Paper Abstract

The objective of the current study is to develop an automatic tool to identify bacterial types using computer-vision and statistical modeling techniques. Bacteriophage (phage)-typing methods are used to identify and extract representative profiles of bacterial types, such as the Staphylococcus Aureus. Current systems rely on the subjective reading of plaque profiles by human expert. This process is time-consuming and prone to errors, especially as technology is enabling the increase in the number of phages used for typing. The statistical methodology presented in this work, provides for an automated, objective and robust analysis of visual data, along with the ability to cope with increasing data volumes.

Paper Details

Date Published: 15 May 2003
PDF: 10 pages
Proc. SPIE 5032, Medical Imaging 2003: Image Processing, (15 May 2003); doi: 10.1117/12.481156
Show Author Affiliations
Sigal Trattner, Tel Aviv Univ. (Israel)
Hayit Greenspan, Tel Aviv Univ. (Israel)
Gapi Tepper, Spring Diagnostics Ltd. (Israel)
Shimon Abboud, Tel Aviv Univ. (Israel)


Published in SPIE Proceedings Vol. 5032:
Medical Imaging 2003: Image Processing
Milan Sonka; J. Michael Fitzpatrick, Editor(s)

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