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Higher Order Variational Methods for Photoacoustic Tomography

Lagerwerf, M.J. (2015) Higher Order Variational Methods for Photoacoustic Tomography.

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Abstract:The goal of this work is to model, implement and test higher order variational methods for photoacoustic tomography. Photoacoustic tomography is a novel imaging method, which is used in breast cancer and rheumatism diagnosis. The challenges in this tomography problem are the robust of handling noise and subsampling on the data and reconstructing difficult data structures. To address those the variational methods using Total Variation and Total Generalized Variation with Bregman iteration are implemented. Moreover, a preconditioned Primal-Dual Hybrid Gradient algorithm is derived to efficiently solve the non-smooth convex minimization problems introduced by these reconstruction models. To show the effectiveness of these methods a careful study is done on both synthetic and experimental data.
Item Type:Essay (Master)
Faculty:EEMCS: Electrical Engineering, Mathematics and Computer Science
Subject:31 mathematics, 44 medicine
Programme:Applied Mathematics MSc (60348)
Link to this item:http://purl.utwente.nl/essays/68151
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