Abstract
Simultaneous Reconstruction and Segmentation (SRS) strategies for computed tomography (CT) present a way to combine the two tasks, which in many applications traditionally are performed as two successive and separate steps. A combined model has a potentially positive effect by allowing the two tasks to influence one another, at the expense of a more complicated algorithm. The combined model increases in complexity due to additional parameters and settings requiring tuning, thus complicating the practical usability. This paper takes it outset in a recently published variational algorithm for SRS. We propose a simplification that reduces the number of required parameters, and we perform numerical experiments investigating the effect and the conditions under which this approach is feasible.
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Acknowledgments
This work is supported by Advanced grant no. 291405 “High-Definition Tomography” from the European Research Council.
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Kjer, H.M., Dong, Y., Hansen, P.C. (2017). User-Friendly Simultaneous Tomographic Reconstruction and Segmentation with Class Priors. In: Lauze, F., Dong, Y., Dahl, A. (eds) Scale Space and Variational Methods in Computer Vision. SSVM 2017. Lecture Notes in Computer Science(), vol 10302. Springer, Cham. https://doi.org/10.1007/978-3-319-58771-4_21
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DOI: https://doi.org/10.1007/978-3-319-58771-4_21
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