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Selecting the reference image for registration of CEST series
Author(s) -
Zhang Yi,
Heo HyeYoung,
Lee DongHoon,
Zhao Xuna,
Jiang Shanshan,
Zhang Kai,
Li Haiyun,
Zhou Jinyuan
Publication year - 2016
Publication title -
journal of magnetic resonance imaging
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.563
H-Index - 160
eISSN - 1522-2586
pISSN - 1053-1807
DOI - 10.1002/jmri.25027
Subject(s) - image registration , artificial intelligence , histogram , computer vision , computer science , pattern recognition (psychology) , nuclear medicine , mathematics , image (mathematics) , medicine
Background To compare different reference images selected for registration among chemical exchange saturation transfer (CEST) series. Materials and Methods Five normal volunteers and eight brain tumor patients were studied on a 3 Tesla scanner. Image registration was performed by choosing each of the acquired CEST saturation or unsaturation dynamic images as the reference. CEST images at 3.5 ppm (amide proton transfer, APT) were computed for each motion‐corrected data set after main magnetic field inhomogeneity correction. A uniformity index was defined to quantify the efficacy of image registration using different reference images. Joint histograms and the structural similarity index (SSIM) were used to analyze the intrinsic image similarity between various dynamic images. Results Image registration increased the average uniformity index by 18% if the 3.5 ppm saturated image was selected as the reference image. However, registering to the unsaturated dynamic image reduced the uniformity index by 13% on average. The joint histogram analysis showed that the saturated dynamic images were highly similar (SSIM = 0.89 ± 0.01), and were considerably different from the unsaturated dynamic image (SSIM = 0.58 ± 0.03). Conclusion The selection of the 3.5 ppm dynamic image as the reference image generated the highest uniformity index for APT imaging though other saturated images were equally suited as reference images. J. MAGN. RESON. IMAGING 2016;43:756–761.