Multidimensional texture analysis for improved prediction of ultrasound liver tumor response to chemotherapy treatment

Depeursinge, Adrien (University of Applied Sciences and Arts Western Switzerland (HES-SO Valais-Wallis) / School of Engineering, Ecole Polytechnique Fédérale de Lausanne (EPFL)) ; Al-Kadi, Omar S. (King Abdullah II School for Information Technology, University of Jordan / School of Engineering, Ecole Polytechnique Fédérale de Lausanne (EPFL)) ; Van De Ville, Dimitri (School of Engineering, Ecole Polytechnique Fédérale de Lausanne (EPFL) / Department of Radiology and Medical Informatics, Université de Genève)

The number density of scatterers in tumor tissue contribute to a heterogeneous ultrasound speckle pattern that can be diffcult to discern by visual observation. Such tumor stochastic behavior becomes even more challenging if the tumor texture heterogeneity itself is investigated for changes related to response to chemotherapy treatment. Here we define a new tumor texture heterogeneity model for evaluating response to treatment. The characterization of the speckle patterns is performed via state-of-the-art multi-orientation and multi-scale circular harmonic wavelet (CHW) frames analysis of the envelope of the radio-frequency signal. The lacunarity measure -corresponding to scatterer number density- is then derived from fractal dimension texture maps within the CHW decomposition, leading to a localized quantitative assessment of tumor texture heterogeneity. Results indicate that evaluating tumor heterogeneity in a multidimensional texture analysis approach could potentially impact on designing an early and effective chemotherapy treatment.

Type de conférence:
full paper
Economie et Services
Institut Informatique de gestion
Adresse bibliogr.:
Athens, Greece, 17th October 2016
Athens, Greece
17th October 2016
8 p.
Publié dans
Proceedings of MICCAI 2016
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