Graphical User Interface (GUI) to Study Different Reconstruction Algorithms in Computed Tomography
2009
- 194Usage
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
- Usage194
- Downloads185
- Abstract Views9
Thesis / Dissertation Description
Computed tomography (CT) imaging relies on computational algorithms to reconstruct images from projections gathered from the CT scan. Depending on the scanner geometry, different types of reconstruction algorithms can be used. To study these different types of reconstruction algorithms in a user-friendly way, a software tool was built. The aim of the thesis was to provide a software platform to access a number of previously implemented reconstruction algorithms with ease and minimal knowledge of the reconstruction code. The goal was accomplished by building a Graphical User Interface (GUI) using MATLAB 7.7.0 (R2008b). In addition to creating mathematical objects and invoking the various reconstruction algorithms, the tool provides newly developed features to analyze the reconstructed images. This thesis first presents an overview of CT and associated reconstruction algorithms. It then describes the features to simulate two-dimensional as well as three-dimensional objects. The reconstructions available are categorized on the basis of different scanner geometries. The tool has the flexibility to specify a range of parameter values for the reconstruction. Finally the tool allows qualitative and quantitative analysis of reconstructed images by using the analysis tool. A couple of test phantoms were simulated to demonstrate the capabilities of the GUI tool. The tests performed included the mask analysis to study the relationship between the standard deviation of reconstructed values and the relevant reconstruction parameters, image subtraction to demonstrate differences in reconstructed values, line profile analysis to show variation of reconstructed image values in more detail, and lastly qualitative image display to visualize reconstruction artifacts using the available reconstruction algorithms. The implemented GUI tool, thus, allows the user to study different reconstruction algorithms with ease using a single panel. It also systematically arranges the available reconstruction algorithms under each scanner geometry. Overall, the tool allows the user to study various objects and reconstruction algorithms by varying different input parameters.
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