Data mining DICOM RT objects for quality control in radiation oncology

Ruchi R. Deshpande; John DeMarco; Daniel Low; Anh H. Le; Brent J. Liu

doi:10.1117/12.911075

16 February 2012 Data mining DICOM RT objects for quality control in radiation oncology

Ruchi R. Deshpande, John DeMarco, Daniel Low, Anh H. Le, Brent J. Liu

Proceedings Volume 8319, Medical Imaging 2012: Advanced PACS-based Imaging Informatics and Therapeutic Applications; 83190Q (2012) https://doi.org/10.1117/12.911075
Event: SPIE Medical Imaging, 2012, San Diego, California, United States

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.

Citation Download Citation

Ruchi R. Deshpande, John DeMarco, Daniel Low, Anh H. Le, and Brent J. Liu "Data mining DICOM RT objects for quality control in radiation oncology", Proc. SPIE 8319, Medical Imaging 2012: Advanced PACS-based Imaging Informatics and Therapeutic Applications, 83190Q (16 February 2012); https://doi.org/10.1117/12.911075

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