PUMA
Istituto di Scienza e Tecnologie dell'Informazione     
Venianaki M., Kontopodis E., Nikiforaki K., De Bree E., Salvetti O., Marias K. A model-free approach for imaging tumor hypoxia from DCE-MRI data. In: CGI'16 - 33rd Computer Graphics International (Heraklion, Crete, 28 June - 1 July 2016). Proceedings, pp. 105 - 108. ACM, 2016.
 
 
Abstract
(English)
Non-invasive imaging biomarkers that assess angiogenic response and tumor microvascular environment at an early stage of therapy could provide useful insights into therapy planning. Tissue hypoxia is related to the insufficient supply of oxygen and is associated with tumor vasculature and perfusion. Thus, knowledge of the hypoxic areas could be of great importance. There is no golden standard for imaging tumor hypoxia yet, however Dynamic Contrast-Enhanced Magnetic Resonance Imaging (DCE-MRI) is among the most promising non-invasive clinically relevant imaging modalities. In this work, DCE-MRI data from neck sarcoma are analyzed through a pattern recognition technique which results in the separation of the tumor area into well-perfused, hypoxic and necrotic regions.
URL: http://dl.acm.org/citation.cfm?id=2949062
DOI: 10.1145/2949035.2949062
Subject DCE-MRI
I.5 PATTERN RECOGNITION
I.4 IMAGE PROCESSING AND COMPUTER VISIONE
15A23 Factorization of matrices


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