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Fourier reconstruction in optoacoustic imaging using truncated regularized inverse k-space interpolation

Michael Jaeger, Simon Schüpbach, Andreas Gertsch, Michael Kitz and Martin Frenz

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A novel Fourier transform based reconstruction algorithm for solving the inverse problem in optoacoustic imaging is presented, which improves reconstruction efficiency and image quality. Fourier algorithms make use of an interpolation law when signal Fourier components are mapped to source Fourier components. To overcome inadequacies affiliated with interpolation methods such as nearest neighbour, linear, cubic or spline interpolation, together with signal data zero padding, we present a regularized interpolation method based on a forward model explicitly formulated for the compactly supported signal data. Simulations performed on a digital tissue phantom reveal the potential of this novel reconstruction method, which results in images of enhanced quality but without the need of using time-consuming zero-padding.


PACS

87.63.D- Ultrasonography

43.80.Qf Medical diagnosis with acoustics (in PACS, see also 87.63.D−)

87.57.C- Image quality

02.30.Zz Inverse problems

02.30.Nw Fourier analysis

87.57.N- Image analysis

MSC

65T40 Trigonometric approximation and interpolation

65R32 Inverse problems

92C55 Biomedical imaging and signal processing (See also 44A12, 65R10)

Subjects

Mathematical physics

Biological physics

Medical physics

Dates

Issue 6 (December 2007)

Received 2 March 2007, in final form 23 May 2007

Published 23 November 2007



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