&lt;title&gt;Image reconstruction in 3D optoacoustic tomography system with hemispherical transducer array&lt;/title&gt;

Андреев, В. Г.; Попов, Д. А.; Sushko, D. V.; Karabutov, Alexander A.; Oraevsky, Alexander A.

doi:10.1117/12.469858

Cited by 11 publications

(7 citation statements)

References 2 publications

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“…On the other hand, if one is in the situation where there is a uniqueness result and all singularities of the object are "visible", one indeed can reconstruct the object stably [13,14,86]. Conditions of unique reconstruction and "visibility" have been also figured out for the case of variable sound speeds and can be expressed simply in terms of geometric optics rays [3,69,77,80,106,124,146,147].…”

Section: Main Mathematical Problems In Tatmentioning

confidence: 99%

Mathematics of Hybrid Imaging: A Brief Review

Kuchment

2012

The Mathematical Legacy of Leon Ehrenpreis

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The article provides a brief survey of the mathematics of newly being developed so called "hybrid" (also called "multi-physics" or "multi-wave") imaging techniques.2. Cost, in the times of the high medical expenses, is clearly one of the major issues. Some imaging techniques (X-ray CT-scan, MRI, PET, and some others) require very expensive devices, with the price tags in millions of dollars. Some others, however, e.g. OT and EIT, are orders of magnitude cheaper. 3.Contrast is another important feature. For instance, if the parameter that a method can detect is, say, electric conductivity of the tissue, then one will be able to distinguish between the tissues that have a significant conductivity contrast and will not see any difference between tissues that happen to have very close electric

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Section: Main Mathematical Problems In Tatmentioning

confidence: 99%

Mathematics of Hybrid Imaging: A Brief Review

Kuchment

2012

The Mathematical Legacy of Leon Ehrenpreis

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“…Such deviations arise, for example, in 3D imaging, if the receiving detection surface is a finite plane. Because of its importance for breast imaging the image reconstruction from data measured on a half circular or hemispherical detector distribution has received much attention (Andreev et al, 2002, Popov and Sushko, 2004). For partly closed detection geometry, where a part of the reconstructed zone is enclosed by the detection surface or curve, it can be shown that sufficient data for a stable reconstruction of all object boundaries are present in a “detection region” (Louis and Quinto, 2000, Xu et al, 2004).…”

Section: Introductionmentioning

confidence: 99%

Weight factors for limited angle photoacoustic tomography

2009

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Photoacoustic tomography (PAT) is based on the generation of ultrasound waves by heating an object with short light pulses. A three-dimensional image of the distribution of absorbed energy within the object is reconstructed from signals measured around the object with either point-like or extended, linear sensors. Limited angle artefacts arise when the curve or surface connecting neighbouring detectors is not closed around the object. For this case, there exists a 'detection region' in which all boundaries of an object are visible in the reconstruction. All straight lines passing through each point in this region intersect the detection curve or surface at least once. Although for these points an accurate reconstruction is possible, direct back projection leads to artefacts when some of the straight lines intersect the detection surface twice and others just once. In this work, special weight functions for direct, non-iterative back projection are presented that reduce these kinds of artefacts. A clear improvement in image quality is shown in simulations for three-dimensional (3D) imaging with point detectors and for two-dimensional (2D) imaging using line detectors compared to reconstruction without weight factors. For the 2D case also an experiment is shown. The presented weight factors make commonly used back projection formulae suitable for a more accurate reconstruction of the initial pressure distribution in cases where the detection aperture only covers a limited angle, and the region of interest lies within the detection region.

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“…Various partial solutions have been suggested: better approximate inverses, corrective coefficients, numerical minimization, using range conditions for recovering the missing data, etc. (e.g., [16,17,19,104]). A recent work in progress (L. Kunyansky, personal communication, January 2008) shows promise for good reconstructions in this case.…”

Section: Theorem 9 [81]mentioning

confidence: 98%