Automatic identification of bacterial types using statistical imaging methods

S. Trattner, H. Greenspan*, G. Tepper, S. Abboud

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review


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.

Original languageEnglish
Pages (from-to)243-252
Number of pages10
JournalProceedings of SPIE - The International Society for Optical Engineering
Volume5032 I
StatePublished - 2003
EventMedical Imaging 2003: Image Processing - San Diego, CA, United States
Duration: 17 Feb 200320 Feb 2003


  • Image analysis
  • Phage typing
  • Spot categorization
  • Spot finding
  • Statistical modeling


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