Original contributionCorrection of intensity nonuniformity in MR images of any orientation
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2021, Medical Image AnalysisSplit Bregman method based level set formulations for segmentation and correction with application to MR images and color images
2019, Magnetic Resonance ImagingCitation Excerpt :In order to eliminate the adverse effect of the bias field on image segmentation, we need to estimate and correct the bias field information in the image. The existing methods of bias correction for MR images are mainly divided into two categories: prospective methods [7-10] and retrospective methods [11-14]. Both methods are to estimate the bias field in the image and divide the original image by the bias field to get the homogeneous image.
Physical correction model for automatic correction of intensity nonuniformity in magnetic resonance imaging
2017, Physics and Imaging in Radiation OncologyA non-iterative multi-scale approach for intensity inhomogeneity correction in MRI
2017, Magnetic Resonance ImagingCitation Excerpt :The major sources of bias field from MRI scanner include static magnetic field inhomogeneity, eddy currents formed by gradient fields, non-uniform reception coil sensitivity etc. Prospective methods include shimming techniques [1], calibration of MRI device by a mathematical model [2], new imaging sequences [3,4]. But, these methods cannot resolve bias field due to magnetic susceptibility of patient anatomy.
Brain MRI Intensity Inhomogeneity Correction Using Region of Interest, Anatomic Structural Map, and Outlier Detection
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