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Book chapter · Conference paper

User-friendly simultaneous tomographic reconstruction and segmentation with class priors

From

Department of Applied Mathematics and Computer Science, Technical University of Denmark1

Visual Computing, Department of Applied Mathematics and Computer Science, Technical University of Denmark2

Scientific Computing, Department of Applied Mathematics and Computer Science, Technical University of Denmark3

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.

Language: English
Publisher: Springer
Year: 2017
Pages: 260-270
Proceedings: 6<sup>th</sup> International Conference on Scale Space and Variational Methods in Computer Vision
Series: Lecture Notes in Computer Science
Journal subtitle: 6th International Conference, Ssvm 2017, Kolding, Denmark, June 4-8, 2017, Proceedings
ISBN: 3319587706 , 3319587714 , 9783319587707 and 9783319587714
ISSN: 03029743
Types: Book chapter and Conference paper
DOI: 10.1007/978-3-319-58771-4_21
ORCIDs: 0000-0003-2503-6475 , Kjer, Hans Martin , Dong, Yiqiu and Hansen, Per Christian

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