Automatic identification of bacterial types using statistical imaging methods

Sigal Trattner; Hayit Greenspan; Gapi Tepper; Shimon Abboud

doi:10.1117/12.481156

15 May 2003 Automatic identification of bacterial types using statistical imaging methods

Sigal Trattner, Hayit Greenspan, Gapi Tepper, Shimon Abboud

Author Affiliations +

Proceedings Volume 5032, Medical Imaging 2003: Image Processing; (2003) https://doi.org/10.1117/12.481156
Event: Medical Imaging 2003, 2003, San Diego, California, United States

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.

Citation Download Citation

Sigal Trattner, Hayit Greenspan, Gapi Tepper, and Shimon Abboud "Automatic identification of bacterial types using statistical imaging methods", Proc. SPIE 5032, Medical Imaging 2003: Image Processing, (15 May 2003); https://doi.org/10.1117/12.481156

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