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Region‐of‐interest reconstruction of motion‐contaminated data using a weighted backprojection filtration algorithm
Author(s) -
King Martin,
Pan Xiaochuan,
Yu Lifeng,
Giger Maryellen
Publication year - 2006
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 - 10.1118/1.2184439
Subject(s) - computer vision , imaging phantom , computer science , artificial intelligence , iterative reconstruction , region of interest , redundancy (engineering) , reconstruction algorithm , projection (relational algebra) , algorithm , image resolution , motion blur , image quality , image (mathematics) , optics , physics , operating system
The recently developed weighted backprojection filtration (WBPF) algorithm using data redundancy has capabilities that make this algorithm an attractive candidate for reconstructing images from motion‐contaminated projection data. First, the WBPF algorithm is capable of reconstructing region‐of‐interest (ROI) images from reduced‐scan fan‐beam data, which have less data than the short‐scan data required to reconstruct the entire field of view (FOV). Second, this algorithm can reconstruct ROI images from truncated data. Using phantom simulation studies, we demonstrate how these unique capabilities can be exploited to reduce the amount of motion‐contaminated data used for reconstruction. In particular, we use examples from cardiac imaging to illustrate how off‐center phantom positioning combined with phase‐interval ROI reconstruction can result in the suppression of motion artifacts. In terms of temporal resolution, reduced‐scan reconstruction with 45% of a full‐scan dataset can be used to improve the temporal resolution of a short‐scan reconstruction by 25.8% if ungated data are used. For data gated at 66 beats per minute , reduced‐scan reconstruction with 45% of a full‐scan dataset can be used to improve the temporal resolution of a short‐scan reconstruction by 7.9%. As a result of our studies, we believe that the WBPF algorithm demonstrates the potential for reconstructing quality ROI images from motion‐contaminated fan‐beam data.