Backprojection inverse filtration for laminographic reconstruction. Issue 9 (1st September 2018)

• Record Type: Journal Article
• Authors: Blumensath, Thomas
• Is Part Of: IET image processing. Volume 12:Issue 9(2018)
• Page Start: 1541
• Page End: 1549
• Publication Date: 2018-09-01
• Subjects: computerised tomography -- image filtering -- image representation -- image reconstruction -- iterative methods -- interpolation -- image restoration -- medical image processing; backprojection inverse filtration -- laminographic reconstruction -- traditional tomography -- circular trajectories -- rotational tomography -- aspect ratios -- filtered backprojection methods -- full iterative reconstruction -- interpolation techniques -- object internal structure estimation -- tomographic projections -- scanning geometry -- projection images -- blurred approximation -- object internal structure representation; Image processing -- Periodicals; 621.36705
• DOI: 10.1049/iet-ipr.2017.1344
• Languages: English
• ISSNs: 1751-9659

Abstract

Abstract : Traditional tomography uses circular trajectories and here, filtered backprojection often works well. However, for objects with large aspect ratios, rotational tomography is often not feasible. In these cases, other trajectories can be more appropriate. For generic trajectories, filtered backprojection methods might not work well and full iterative reconstruction can be computationally demanding. In this study, the authors thus propose a third paradigm that combines aspects of both of these techniques. They use interpolation and backprojection techniques to generate an initial estimate of an object's internal structure using projection images taken at different orientations. Depending on the scanning geometry used to calculate the tomographic projections, this initial estimate can be understood as a blurred (filtered) approximation of the actual structure. For each scanning geometry, they specify the equivalent blurring operator that would provide the same estimate directly from a representation of the object's internal structure. They then use iterative techniques to invert this filtering operation, thus estimating the internal structure from the estimate of its blurred representation.