
Proceedings Paper
Edge-masked CT image reconstruction from limited dataFormat | Member Price | Non-Member Price |
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Paper Abstract
This paper presents a preliminary investigation of an iterative inversion algorithm for computed tomography image reconstruction that early results show performs well in terms of accuracy and speed using limited data. The computational method combines an image domain technique and statistical reconstruction by using an initial filtered back projection reconstruction to create a binary edge mask, which is then used in a weighted ℓ2-regularized reconstruction. Both theoretical and empirical results are offered to support the algorithm. While in this paper a simple forward model is used and physical edges are used as the sparse feature, the proposed method is flexible and can accommodate any forward model and sparsifying transform.
Paper Details
Date Published: 28 May 2019
PDF: 5 pages
Proc. SPIE 11072, 15th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine, 110721V (28 May 2019); doi: 10.1117/12.2534436
Published in SPIE Proceedings Vol. 11072:
15th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine
Samuel Matej; Scott D. Metzler, Editor(s)
PDF: 5 pages
Proc. SPIE 11072, 15th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine, 110721V (28 May 2019); doi: 10.1117/12.2534436
Show Author Affiliations
Victor Churchill, Dartmouth College (United States)
Anne Gelb, Dartmouth College (United States)
Published in SPIE Proceedings Vol. 11072:
15th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine
Samuel Matej; Scott D. Metzler, Editor(s)
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