A large-scale graph processing system for medical imaging information based on DICOM-SR. (2015)

• Record Type: Journal Article
• Authors: Torres-Serrano, Erik
• Is Part Of: International journal of image mining. Volume 1:Number 2/3(2015)
• Page Start: 143
• Page End: 158
• Publication Date: 2015
• Subjects: large-scale graph processing -- cloud-based data processing -- medical reports -- data integration -- medical imaging -- DICOM-SR -- cloud computing -- healthcare technology -- big data analysis -- radiology -- medical information retrieval; Image processing -- Periodicals; Data mining -- Periodicals; 006.42
• Languages: English
• ISSNs: 2055-6039

Abstract

This paper presents Gpf4Med, a framework for the integration and analysis of medical reports, which aims at becoming a useful tool in healthcare research. Gpf4Med was designed to address big data analysis, considering the actual trends of exponential data growth and the explosion of data formats. Solutions are proposed from the point of view of the architecture design of the framework to face these problems. Preliminary studies are presented with very promising results for the applicability of the framework to the identification of non-evident correlations in the reports, while maintaining the desired levels of usability and performance that will allow radiologists and other possible users and stakeholders to useGpf4Med in their daily work. Additional works are in progress to enhance the framework with more complex algorithms to discover clinically relevant information in wide-disease analysis of large datasets of medical reports.