Uncertainty Based Adaptive Projection Selection Strategy for Binary Tomographic Reconstruction

• Published in: Computer Analysis of Images and Patterns Vol. 11679; pp. 74 - 84
• Main Authors: Lékó, Gábor, Domány, Szilveszter, Balázs, Péter
• Format: Book Chapter
• Language: English
• Published: Switzerland Springer International Publishing AG 2019; Springer International Publishing
• Series: Lecture Notes in Computer Science
• Subjects: Adaptive projection selection; Binary tomography; Online projection selection; Reconstruction; Uncertainty
• ISBN: 3030298906; 9783030298906
• ISSN: 0302-9743; 1611-3349
• DOI: 10.1007/978-3-030-29891-3_7

The goal of binary tomography is to examine the inner structure of homogeneous objects based on their projections. The 2D slices of the objects can be represented by binary matrices and the aim is to recreate these matrices from a collection of their line sums. For cost-effectiveness and speed reasons it is worth to do the reconstruction from as few projections as possible while still maintaining an acceptable image quality. The key is to specify the most informative projection angles. In this paper we propose a reconstruction uncertainty based adaptive (online) projection selection method for binary tomographic reconstruction. We compare our algorithm to other already published methods.