An automated DICOM database capable of arbitrary data mining (Including Radiation Dose Indicators) for quality monitoring

Shanshan Wang, William Pavlicek, Catherine C. Roberts, Steve G. Langer, Muhong Zhang, Mengqi Hu, Richard L. Morin, Beth A. Schueler, Clinton V. Wellnitz, Teresa Wu

Research output: Contribution to journalArticle

37 Scopus citations

Abstract

The U.S. National Press has brought to full public discussion concerns regarding the use of medical radiation, specifically x-ray computed tomography (CT), in diagnosis. A need exists for developing methods whereby assurance is given that all diagnostic medical radiation use is properly prescribed, and all patients' radiation exposure is monitored. The "DICOM Index Tracker

Original languageEnglish (US)
Pages (from-to)223-233
Number of pages11
JournalJournal of Digital Imaging
Volume24
Issue number2
DOIs
StatePublished - Apr 2011

Keywords

  • Data extraction
  • Database management systems
  • Knowledge base
  • Medical informatics applications
  • Radiation dose

ASJC Scopus subject areas

  • Radiological and Ultrasound Technology
  • Radiology Nuclear Medicine and imaging
  • Computer Science Applications

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    Wang, S., Pavlicek, W., Roberts, C. C., Langer, S. G., Zhang, M., Hu, M., Morin, R. L., Schueler, B. A., Wellnitz, C. V., & Wu, T. (2011). An automated DICOM database capable of arbitrary data mining (Including Radiation Dose Indicators) for quality monitoring. Journal of Digital Imaging, 24(2), 223-233. https://doi.org/10.1007/s10278-010-9329-y