A novel, fast entropy-minimization algorithm for bias field correction in MR images

@article{citeulike:1495813, abstract = {A novel, fast entropy-minimization algorithm for bias field correction in magnetic resonance (MR) images is suggested to correct the intensity inhomogeneity degradation of MR images that has become an increasing problem with the use of phased-array coils. Four important modifications were made to the conventional algorithm: (a) implementation of a modified two-step sampling strategy for stacked 2D image data sets, which included reducing the size of the measured image on each slice with a simple averaging method without changing the number of slices and then using a binary mask generated by a histogram threshold method to define the sampled voxels in the reduced image; (b) improvement of the efficiency of the correction function by using a Legendre polynomial as an orthogonal base function polynomial; (c) use of a nonparametric Parzen window estimator with a Gaussian kernel to calculate the probability density function and Shannon entropy directly from the image data; and (d) performing entropy minimization with a conjugate gradient method. Results showed that this algorithm could correct different types of MR images from different types of coils acquired at different field strengths very efficiently and with decreased computational load.}, author = {Ji, Qing and Glass, John O. and Reddick, Wilburn E. }, citeulike-article-id = {1495813}, doi = {http://dx.doi.org/10.1016/j.mri.2006.09.012}, journal = {Magnetic Resonance Imaging}, keywords = {bias, correction, inhomogeneity, mri}, month = {February}, number = {2}, pages = {259--264}, posted-at = {2007-07-26 13:37:52}, priority = {2}, title = {A novel, fast entropy-minimization algorithm for bias field correction in MR images}, url = {http://dx.doi.org/10.1016/j.mri.2006.09.012}, volume = {25}, year = {2007} }

TY - JOUR ID - citeulike:1495813 L3 - citeulike-article-id:1495813 TI - A novel, fast entropy-minimization algorithm for bias field correction in MR images JF - Magnetic Resonance Imaging VL - 25 IS - 2 SP - 259 EP - 264 N2 - A novel, fast entropy-minimization algorithm for bias field correction in magnetic resonance (MR) images is suggested to correct the intensity inhomogeneity degradation of MR images that has become an increasing problem with the use of phased-array coils. Four important modifications were made to the conventional algorithm: (a) implementation of a modified two-step sampling strategy for stacked 2D image data sets, which included reducing the size of the measured image on each slice with a simple averaging method without changing the number of slices and then using a binary mask generated by a histogram threshold method to define the sampled voxels in the reduced image; (b) improvement of the efficiency of the correction function by using a Legendre polynomial as an orthogonal base function polynomial; (c) use of a nonparametric Parzen window estimator with a Gaussian kernel to calculate the probability density function and Shannon entropy directly from the image data; and (d) performing entropy minimization with a conjugate gradient method. Results showed that this algorithm could correct different types of MR images from different types of coils acquired at different field strengths very efficiently and with decreased computational load. KW - bias KW - correction KW - inhomogeneity KW - mri AU - Ji, Qing AU - Glass, John AU - Reddick, Wilburn PY - 2007/02// UR - http://dx.doi.org/10.1016/j.mri.2006.09.012 ER -