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From Image Data to Three-Dimensional Models - Case Studies on the Impact of 3D Patient Models
(2002)
Dual Streamline Seeding
(2009)
In civil engineering, the corrosion of steel reinforcements in structural elements of concrete bares a risk of
stability-reduction, mainly caused by the exposure to chlorides. 3D computed tomography (CT) reveals the inner
structure of concrete and allows one to investigate the corrosion with non-destructive testing methods. To carry
out such investigations, specimens with a large artificial crack and an embedded steel rebar have been
manufactured. 3D CT images of those specimens were acquired in the original state. Subsequently three cycles
of electrochemical pre-damaging together with CT imaging were applied. These time series have been evaluated
by means of image processing algorithms to segment and quantify the corrosion products. Visualization of the
results supports the understanding of how corrosion propagates into cracks and pores. Furthermore, pitting of
structural elements can be seen without dismantling. In this work, several image processing and visualization
techniques are presented that have turned out to be particularly effective for the visualization and segmentation
of corrosion products. Their combination to a workflow for corrosion analysis is the main contribution of this
work.
The goal of quantitative photoacoustic tomography (qPAT) is to recover maps of the chromophore distributions from multiwavelength images of the initial pressure. Model-based inversions that incorporate the physical processes underlying the photoacoustic (PA) signal generation represent a promising approach. Monte-Carlo models of the light transport are computationally expensive, but provide accurate fluence distributions predictions, especially in the ballistic and quasi-ballistic regimes. Here, we focus on the inverse problem of 3D qPAT of blood oxygenation and investigate the application of the Monte-Carlo method in a model-based inversion scheme. A forward model of the light transport based on the MCX simulator and acoustic propagation modeled by the k-Wave toolbox was used to generate a PA image data set acquired in a tissue phantom over a planar detection geometry. The combination of the optical and acoustic models is shown to account for limited-view artifacts. In addition, the errors in the fluence due to, for example, partial volume artifacts and absorbers immediately adjacent to the region of interest are investigated. To accomplish large-scale inversions in 3D, the number of degrees of freedom is reduced by applying image segmentation to the initial pressure distribution to extract a limited number of regions with homogeneous optical parameters. The absorber concentration in the tissue phantom was estimated using a coordinate descent parameter search based on the comparison between measured and modeled PA spectra. The estimated relative concentrations using this approach lie within 5 % compared to the known concentrations. Finally, we discuss the feasibility of this approach to recover the blood oxygenation from experimental data.
Quantitative photoacoustic tomography (qPAT) aims to extract physiological parameters, such as blood oxygen saturation (sO2), from measured multi-wavelength image data sets. The challenge of this approach lies in the inherently nonlinear fluence distribution in the tissue, which has to be accounted for by using an appropriate model, and the large scale of the inverse problem. In addition, the accuracy of experimental and scanner-specific parameters, such as the wavelength dependence of the incident fluence, the acoustic detector response, the beam profile and divergence, needs to be considered. This study aims at quantitative imaging of blood sO2, as it has been shown to be a more robust parameter compared to absolute concentrations. We propose a Monte-Carlo–based inversion scheme in conjunction with a reduction in the number of variables achieved using image segmentation. The inversion scheme is experimentally validated in tissue-mimicking phantoms consisting of polymer tubes suspended in a scattering liquid. The tubes were filled with chromophore solutions at different concentration ratios. 3-D multi-spectral image data sets were acquired using a Fabry-Perot based PA scanner. A quantitative comparison of the measured data with the output of the forward model is presented. Parameter estimates of chromophore concentration ratios were found to be within 5 % of the true values.
Automated 3D Crack Detection for Analyzing Damage Processes in Concrete with Computed Tomography
(2012)