Computer-assisted identification and volumetric quantification of dynamic contrast enhancement in brain MRI: an interactive system

Shandong Wu; Nicholas G. Avgeropoulos; David J. Rippe

doi:10.1117/12.2008163

29 March 2013 Computer-assisted identification and volumetric quantification of dynamic contrast enhancement in brain MRI: an interactive system

Shandong Wu, Nicholas G. Avgeropoulos, David J. Rippe

Author Affiliations +

Proceedings Volume 8674, Medical Imaging 2013: Advanced PACS-based Imaging Informatics and Therapeutic Applications; 867407 (2013) https://doi.org/10.1117/12.2008163
Event: SPIE Medical Imaging, 2013, Lake Buena Vista (Orlando Area), Florida, United States

Abstract

We present a dedicated segmentation system for tumor identification and volumetric quantification in dynamic contrast brain magnetic resonance (MR) scans. Our goal is to offer a practically useful tool at the end of clinicians in order to boost volumetric tumor assessment. The system is designed to work in an interactive mode such that maximizes the integration of computing capacity and clinical intelligence. We demonstrate the main functions of the system in terms of its functional flow and conduct preliminary validation using a representative pilot dataset. The system is inexpensive, user-friendly, easy to deploy and integrate with picture archiving and communication systems (PACS), and possible to be open-source, which enable it to potentially serve as a useful assistant for radiologists and oncologists. It is anticipated that in the future the system can be integrated into clinical workflow so that become routine available to help clinicians make more objective interpretations of treatment interventions and natural history of disease to best advocate patient needs.

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Shandong Wu, Nicholas G. Avgeropoulos, and David J. Rippe "Computer-assisted identification and volumetric quantification of dynamic contrast enhancement in brain MRI: an interactive system", Proc. SPIE 8674, Medical Imaging 2013: Advanced PACS-based Imaging Informatics and Therapeutic Applications, 867407 (29 March 2013); https://doi.org/10.1117/12.2008163

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KEYWORDS

Tumors

Image segmentation

Brain

Magnetic resonance imaging

Visualization

Computing systems

Human-machine interfaces

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