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Abstract #2439

Evaluation of MR Image Intensity Inhomogeneity Correction Algorithms

Jinghua Wang1, Lili He2, Zhong-lin Lu3

1Center for Cognitive and Behavioral Brain Imaging, The Ohio State Univeristy, Columbus, OH, United States; 2Center for Perinatal Research, Nationwide Children's Hospital, Columbus, OH, United States; 3Center for Cognitive and Behavioral Brain Imaging, The Ohio State University, Columbus, OH, United States

MR image intensity inhomogeneity has rendered quantitative MRI analysis in anatomical studies a major challenge. Various methods for performing inhomogeneity correction have been proposed. Evaluation of these methods has often relied on subjective assessment because of the lack of the ground truth. Here, we present a new method to evaluate four popular inhomogeneity correction methods based on both uniform phantom and in vivo brain images. We found that the field map method outperformed the others. This method can be used to guide parameter optimization for existing correction methods, improve bias field modeling, and evaluate and optimize new correction methods.