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A residual correction method for high‐resolution PET reconstruction with application to on‐the‐fly Monte Carlo based model of positron range
Author(s) -
Fu Lin,
Qi Jinyi
Publication year - 2010
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1118/1.3284980
Subject(s) - residual , iterative reconstruction , monte carlo method , computer science , computation , algorithm , image resolution , tomographic reconstruction , reconstruction algorithm , a priori and a posteriori , projection (relational algebra) , image quality , matrix (chemical analysis) , algebraic reconstruction technique , maximum a posteriori estimation , iterative method , computer vision , artificial intelligence , image (mathematics) , mathematics , maximum likelihood , philosophy , statistics , materials science , epistemology , composite material
Purpose: The quality of tomographic images is directly affected by the system model being used in image reconstruction. An accurate system matrix is desirable for high‐resolution image reconstruction, but it often leads to high computation cost. In this work the authors present a maximum a posteriori reconstruction algorithm with residual correction to alleviate the tradeoff between the model accuracy and the computation efficiency in image reconstruction. Methods: Unlike conventional iterative methods that assume that the system matrix is accurate, the proposed method reconstructs an image with a simplified system matrix and then removes the reconstruction artifacts through residual correction. Since the time‐consuming forward and back projection operations using the accurate system matrix are not required in every iteration, image reconstruction time can be greatly reduced. Results: The authors apply the new algorithm to high‐resolution positron emission tomography reconstruction with an on‐the‐fly Monte Carlo (MC) based positron range model. Computer simulations show that the new method is an order of magnitude faster than the traditional MC‐based method, whereas the visual quality and quantitative accuracy of the reconstructed images are much better than that obtained by using the simplified system matrix alone. Conclusions: The residual correction method can reconstruct high‐resolution images and is computationally efficient.