Edge-masked CT image reconstruction from limited data

Victor Churchill; Anne Gelb

doi:10.1117/12.2534436

28 May 2019 Edge-masked CT image reconstruction from limited data

Victor Churchill, Anne Gelb

Proceedings Volume 11072, 15th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine; 110721V (2019) https://doi.org/10.1117/12.2534436
Event: Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine, 2019, Philadelphia, United States

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.

Citation Download Citation

Victor Churchill and Anne Gelb "Edge-masked CT image reconstruction from limited data", Proc. SPIE 11072, 15th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine, 110721V (28 May 2019); https://doi.org/10.1117/12.2534436

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