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Technical Note: Intrinsic raw data‐based CT misalignment correction without redundant data
Author(s) -
Sawall Stefan,
Hahn Andreas,
Maier Joscha,
Kuntz Jan,
Kachelrieß Marc
Publication year - 2019
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 - 10.1002/mp.13254
Subject(s) - imaging phantom , computer science , iterative reconstruction , range (aeronautics) , computer vision , projection (relational algebra) , raw data , image quality , calibration , artificial intelligence , algorithm , image (mathematics) , mathematics , optics , physics , engineering , statistics , programming language , aerospace engineering
Purpose CT image reconstruction requires accurate knowledge of the used geometry or image quality might be degraded by misalignment artifacts. To overcome this issue, an intrinsic method, that is, a method not requiring a dedicated calibration phantom, to perform a raw data‐based misalignment correction for CT is proposed herein that does not require redundant data and hence is applicable to measurements with less than 180 ∘ plus fan–angle of data. Methods The forward projection of a volume reconstructed from a misaligned geometry resembles the acquired raw data if no redundant data are used, that is, if less than 180 ∘ plus fan–angle are used for image reconstruction. Hence, geometric parameters cannot be deduced from such data by an optimization of the geometry‐dependent raw data fidelity. We propose to use a nonlinear transform applied to the reconstructed volume to introduce inconsistencies in the raw data that can be employed to estimate geometric parameters using less than 180 ∘ plus fan–angle of data. The proposed method is evaluated using simulations of the FORBILD head phantom and using actual measurements of a contrast‐enhanced scan of a mouse acquired using a micro‐CT. Results Noisy simulations and actual measurements demonstrate that the proposed method is capable of correcting for artifacts arising from a misaligned geometry without redundant data while ensuring raw data fidelity. Conclusions The proposed method extends intrinsic raw data‐based misalignment correction methods to an angular range of 180 ∘ or less and is thus applicable to systems with a limited scan range.