A New Scale Space Total Variation Algorithm for Limited Angle Tomography

Huang Y, Taubmann O, Huang X, Haase V, Lauritsch G, Maier A (2016)

Publication Language: English

Publication Type: Conference contribution, Original article

Publication year: 2016

Publisher: IEEE

Pages Range: 149-152

Conference Proceedings Title: CT-Meeting 2016 Proceedings (The 4th International Meeting on Image Formation in X-Ray Computed Tomography)

Event location: Bamberg, Germany

URI: https://www5.informatik.uni-erlangen.de/Forschung/Publikationen/2016/Huang16-ANS.pdf

Abstract

This paper proposes a scale space total variation (ssTV) algorithm to reduce large scale streaks in limited angle tomography. The weighted total variation (wTV) algorithm is able to remove most small scale streaks. However, it fails to reduce larger streaks since total variation (TV) regularization is scale-dependent and may regard them as homogeneous areas. Derived from the wTV algorithm, the proposed ssTV algorithm applies wTV regularization on the image at different scales using down-sampling and up-sampling operations and thus can reduce streaks more effectively. Advantages of the ssTV algorithm are demonstrated on both 2-D numerical data and a 3-D clinical dataset.

Authors with CRIS profile

Involved external institutions

Siemens AG, Healthcare Sector Germany (DE)

How to cite

APA:

Huang, Y., Taubmann, O., Huang, X., Haase, V., Lauritsch, G., & Maier, A. (2016). A New Scale Space Total Variation Algorithm for Limited Angle Tomography. In Marc Kachelrieß (Eds.), CT-Meeting 2016 Proceedings (The 4th International Meeting on Image Formation in X-Ray Computed Tomography) (pp. 149-152). Bamberg, Germany: IEEE.

MLA:

Huang, Yixing, et al. "A New Scale Space Total Variation Algorithm for Limited Angle Tomography." Proceedings of the CT-Meeting 2016, Bamberg, Germany Ed. Marc Kachelrieß, IEEE, 2016. 149-152.

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