Abstract
In some cases of tomography we can only gain high resolution projections of the object with only partial coverage, whereas only a small part of the object – a given Region of Interest (ROI) – is fully covered by high resolution projections. In such cases the structures outside the region of interest cause artefacts to appear in the reconstructed image and degrade the image quality of the tomogram. We proposed three new iterative approaches for the accurate reconstruction of the ROI by combining a high resolution set of projections, with low resolution full field of view projections and prior information. We also evaluate our methods reconstructing software phantoms, and compare their performance to other methods in the literature.
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Acknowledgement
This research was supported by the project “Integrated program for training new generation of scientists in the fields of computer science”, no EFOP-3.6.3-VEKOP-16-2017-0002. The project has been supported by the European Union and co-funded by the European Social Fund. We gratefully acknowledge the support of NVIDIA Corporation with the donation of a Tesla K40 GPU used for this research.
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Varga, L., Mokso, R. (2018). Iterative High Resolution Tomography from Combined High-Low Resolution Sinogram Pairs. In: Barneva, R., Brimkov, V., Tavares, J. (eds) Combinatorial Image Analysis. IWCIA 2018. Lecture Notes in Computer Science(), vol 11255. Springer, Cham. https://doi.org/10.1007/978-3-030-05288-1_12
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DOI: https://doi.org/10.1007/978-3-030-05288-1_12
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