A meta method for image matching

Sharmishtaa Seshamani, Rajesh Kumar, Gerard Mullin, Themistocles Dassopoulos, Gregory D. Hager

Research output: Contribution to journalArticlepeer-review


This paper presents a novel system for image matching in optical endoscopy. The proposed metamatching system approaches the challenge of matching images in a complex scene by incorporating multiple matchers and a decision function. Experiments are presented for Crohn's disease lesion matching in capsule endoscopy with a metamatcher consisting of five independent matchers. We compare the performance of six different types of decision functions. Results show that the F-measure of the metamatching system containing all five matchers is 4%-7% greater than the performance of using the best matcher only, with a maximum F-measure of 0.811. The robustness of the method is validated using simulated data generated by controlled deformations of the image. We also demonstrate how the addition of simulated data to the training set can be used to augment the performance of the metamatcher by up to 10%.

Original languageEnglish (US)
Article number5720317
Pages (from-to)1468-1479
Number of pages12
JournalIEEE transactions on medical imaging
Issue number8
StatePublished - Aug 2011


  • Endoscopy
  • image matching
  • meta methods

ASJC Scopus subject areas

  • Software
  • Radiological and Ultrasound Technology
  • Computer Science Applications
  • Electrical and Electronic Engineering


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