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The raw data were corrected for differences using a total lane intensity correction.
The k-space energy-anchored EPI data (with Type 1 artifacts inherently eliminated) were reconstructed with the KESA-based multischeme partial-Fourier reconstruction method to correct for Type 2 artifacts, and the signal intensity correction was subsequently performed to minimize Type 3 artifacts.
Nevertheless, the very minor residual Type 2 and Type 3 artifacts were corrected with the multischeme partial-Fourier reconstruction and signal intensity correction, respectively, before averaging the four sets of magnitude images.
High-resolution anatomical images were used after non-uniform intensity correction to create cortical surface reconstructions of both lesioned and normal hemispheres.
Quality control, data preprocessing and background signal intensity correction was performed to yield a ratio of methylated and unmethylated signal intensities, followed by detailed bioinformatic and statistical analyses.
Both wavelength calibration and intensity correction are adopted to eliminate the influence of nonlinear sensitivity from CMOS camera.
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The precipitate morphology was reconstructed using a multi-step image-processing approach, including registration, intensity corrections, segmentation and segmentation cleanup.
Properly choosing both wavelength and sample thickness allows absorption to be kept to an acceptable value, avoiding peak shift and intensity corrections.
The microarrays were scanned, and feature extraction and background intensity corrections were performed with Agilent software (v.10.7.3.1).
After the intensity corrections and skull stripping, a researcher blind to the condition of each subject manually corrected the images.
Data processing was carried out using the self-implemented software package PyGid, including intensity corrections according to ref (66) and a correction of refraction effects.
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