Classification of Radiographs in the 'Image Retrieval in Medical Applications' - System

@inproceedings{Dahmen2000ClassificationOR,
  title={Classification of Radiographs in the 'Image Retrieval in Medical Applications' - System},
  author={J{\"o}rg Dahmen and Thomas Theiner and Daniel Keysers and Thomas Martin Deserno and Berthold B. Wein},
  booktitle={RIAO},
  year={2000}
}
In this paperwe presenta new approachto classifyingradiographs,which is the first importanttaskof the IRMA system.Given an image,we computeposteriorprobabilitiesfor eachimageclass,asthis informationis neededfor further IRMA processing.Classificationis doneby usinganextendedversionof Simard’s tangentdistancewithin a kerneldensitybasedclassifier . We proposea new distortionmodelfor radiographsandproveits effectivenessby applyingthemethodto 1617radiographscomingfrom daily routine… CONTINUE READING
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References

Publications referenced by this paper.
Showing 1-4 of 4 references

Manmatha,“On ComputingGlobalSimilarity in Images”,Proceedingsof theIEEEWorkshoponApplicationsof ComputerVision(WACV), pp. 82-87,Princeton,NJ,October1998

  • Ravela, Manmatha, R. 1998 S. Ravela
  • 1998

AutomatedPACSImageAquisitionand Recovery Schemefor ImageIntegrity Basedon theDICOM Standard”,ComputerizedMedical ImagingandGraphics,Vol.21,No.4,pp.209-218.1997

  • H. Huang, “An
  • 1997

Local GrayvalueInvariantsfor ImageRetrieval”, IEEETransactionsonPatternRecognitionandMachineIntelligence,Vol

  • Schmid, Mohr
  • 1997

Hafneret al., “Efficient andEffective Queryingby ImageContent”,Journalof

  • J. M. Flickner
  • Intelligent InformationSystems,Vol.3,
  • 1994

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