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Proceedings Paper

Data mining DICOM RT objects for quality control in radiation oncology
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Paper Abstract

Our goal in this paper is to data mine the wealth of information contained in the dose-volume objects used in external beam radiotherapy treatment planning. In addition, by performing computational pattern recognition on these mined objects, the results may help identify predictors for unsafe dose delivery. This will ultimately enhance current clinical registries by the inclusion of detailed dose-volume data employed in treatments. The most efficient way of including dose-volume information in a registry is through DICOM RT objects. With this in mind, we have built a DICOM RT specific infrastructure, capable of integrating with larger, more general clinical registries, and we will present the results of data mining these sets.

Paper Details

Date Published: 16 February 2012
PDF: 9 pages
Proc. SPIE 8319, Medical Imaging 2012: Advanced PACS-based Imaging Informatics and Therapeutic Applications, 83190Q (16 February 2012); doi: 10.1117/12.911075
Show Author Affiliations
Ruchi R. Deshpande, The Univ. of Southern California (United States)
John DeMarco, Univ. of California, Los Angeles (United States)
Daniel Low, Univ. of California, Los Angeles (United States)
Anh H. Le, Univ. of Pittsburgh (United States)
Brent J. Liu, The Univ. of Southern California (United States)


Published in SPIE Proceedings Vol. 8319:
Medical Imaging 2012: Advanced PACS-based Imaging Informatics and Therapeutic Applications
William W. Boonn; Brent J. Liu, Editor(s)

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