Abstract
Several limited data problems in tomography will be presented in this chapter, including ones for X-ray tomography, electron microscopy, and radar imaging. First, reconstructions from limited data will be evaluated to observe their strengths and weaknesses. Then, the basic analytic properties of the transforms will be presented. The concept of microlocal analysis will be introduced to make the notion of singularity precise. Finally, the microlocal properties of the tomographic transforms are given and then used to explain the observed strengths and limitations of the reconstructions. This will show that these limitations are intrinsic to these limited data problems themselves.
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Acknowledgements
Both authors thank the American Institute of Mathematics and their colleaguesGaik Ambartsoumian, Raluca Felea, and Clifford Nolan in an American Instituteof Mathematics (AIM) SQuaREs program for discussions at AIM on microlocalanalysis and radar imaging that informed this work. They appreciate JürgenFrikel’s careful reading of the chapter. The authors thank the MittagLeffler Institute for the congenial atmosphere as they worked on some ofthe research presented in this chapter. The second named author thanksJan Boman, Alfred Louis, Frank Natterer, and many other friends andcolleagues for important discussions about tomography and microlocalanalysis over the years. Both authors thank Birsen Yazıcı for interestingdiscussions.
The first named author was partially supported by NSF grant DMS 1109417. Additionally, he benefited from the support of Airbus Group Corporate Foundation Chair in “Mathematics of Complex Systems” established at TIFR CAM and ICTS TIFR, Bangalore, India, and from a German DAAD Research Stays grant. The second named author was partially supported by NSF grant DMS 1311558.
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Krishnan, V.P., Quinto, E.T. (2015). Microlocal Analysis in Tomography. In: Scherzer, O. (eds) Handbook of Mathematical Methods in Imaging. Springer, New York, NY. https://doi.org/10.1007/978-1-4939-0790-8_36
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