Interactive visual analysis of contrast-enhanced ultrasound data based on local neighborhood statistics

Paolo Angelelli, Kim Nylund, Odd Helge Gilja, Helwig Hauser
Department of Informatics, University of Bergen, Norway
Computers & Graphics (22 December 2010)


   title={Interactive visual analysis of contrast-enhanced ultrasound data based on local neighborhood statistics},

   author={Angelelli, P. and Nylund, K. and Helge Gilja, O. and Hauser, H.},

   journal={Computers & Graphics},





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Contrast-enhanced ultrasound (CEUS) has recently become an important technology for lesion detection and characterization in cancer diagnosis. CEUS is used to investigate the perfusion kinetics in tissue over time, which relates to tissue vascularization. In this paper we present a pipeline that enables interactive visual exploration and semi-automatic segmentation and classification of CEUS data. For the visual analysis of this challenging data, with characteristic noise patterns and residual movements, we propose a robust method to derive expressive enhancement measures from small spatio-temporal neighborhoods. We use this information in a staged visual analysis pipeline that leads from a more local investigation to global results such as the delineation of anatomic regions according to their perfusion properties. To make the visual exploration interactive, we have developed an accelerated framework based on the OpenCL library, that exploits modern many-cores hardware. Using our application, we were able to analyze datasets from CEUS liver examinations, being able to identify several focal liver lesions, segment and analyze them quickly and precisely, and eventually characterize them.
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