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01.04.2016 | Medical Information Retrieval

Retrieval, visualization, and mining of large radiation dosage data

verfasst von: William Kovacs, Samuel Weisenthal, Les Folio, Qiaoyi Li, Ronald M. Summers, Jianhua Yao

Erschienen in: Discover Computing | Ausgabe 1-2/2016

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Abstract

Radiation dose monitoring has become an essential service that hospitals must perform. Depending on the system in place, this can result in the collection of large quantities of data, ripe for analysis. These data should include a wide variety of variables for each study because assessment of the propriety of the patient’s dose is dependent on many factors, including patient age and size, as well as the body section that is being scanned. Moreover, the scanners themselves have many properties that affect patient dose, such as model, pitch and kVp. In this paper, we propose an engine that seamlessly integrated with a clinical PACS to retrieve radiation dosage data. We devised several schemes to analyze these data through visualization and mining techniques that examine it at different scopes. We demonstrate the utility of such visual methods at examining large, noisy, and multi-dimensional data, which is embodied in the collected radiation data.

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Titel: Retrieval, visualization, and mining of large radiation dosage data
verfasst von: William Kovacs
Samuel Weisenthal
Les Folio
Qiaoyi Li
Ronald M. Summers
Jianhua Yao
Publikationsdatum: 01.04.2016
Verlag: Springer Netherlands
Erschienen in: Discover Computing / Ausgabe 1-2/2016
Print ISSN: 2948-2984
Elektronische ISSN: 2948-2992
DOI: https://doi.org/10.1007/s10791-015-9265-z

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