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Improved field‐mapping and artifact correction in multispectral imaging
Author(s) -
Quist Brady,
Shi Xinwei,
Weber Hans,
Hargreaves Brian A.
Publication year - 2017
Publication title -
magnetic resonance in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.696
H-Index - 225
eISSN - 1522-2594
pISSN - 0740-3194
DOI - 10.1002/mrm.26597
Subject(s) - deblurring , multispectral image , imaging phantom , artificial intelligence , artifact (error) , computer science , noise (video) , distortion (music) , computer vision , pattern recognition (psychology) , image restoration , image processing , image (mathematics) , nuclear medicine , medicine , amplifier , computer network , bandwidth (computing)
Purpose To develop a method for improved B 0 field‐map estimation, deblurring, and image combination for multispectral imaging near metal. Methods A goodness‐of‐fit field‐map estimation technique is proposed that uses only the multispectral imaging (MSI) data to estimate the field map. Using the improved field map, a novel deblurring technique is proposed that also employs a new image combination scheme to reduce the effects of noise and other residual MSI artifacts. The proposed field‐map estimation and deblurring techniques are compared to the current methods in phantoms and/or in vivo from subjects with knee, hip, and spinal metallic implants. Results Phantom experiments validate that the goodness‐of‐fit field‐map estimation is less sensitive to noise and bias than the conventional center‐of‐mass technique, which reduces distortion in the deblurring methods. The new deblurring approach also is substantially less sensitive to noise and distortion than the current deblurring method, as demonstrated in phantoms and in vivo, and is able to find a good tradeoff between deblurring and distortion. Conclusion The proposed methods not only enable field‐mapping with reduced noise sensitivity but are able to create deblurred images with less distortion and better signal‐to‐noise ratio with no additional scan time, thereby enabling improved visualization of underlying anatomy near metallic implants. Magn Reson Med 78:2022–2034, 2017. © 2017 International Society for Magnetic Resonance in Medicine.