A nonparametric method for automatic correction of intensity nonuniformity in MRI data

• Published in: IEEE transactions on medical imaging Vol. 17; no. 1; pp. 87 - 97
• Main Authors: Sled, J.G., Zijdenbos, A.P., Evans, A.C.
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.02.1998; Institute of Electrical and Electronics Engineers
• Subjects: Anatomy; Biological and medical sciences; Brain; Brain - anatomy & histology; Coils; Computer simulation; Data analysis; Humans; Image analysis; In vivo; Investigative techniques, diagnostic techniques (general aspects); Iterative methods; Magnetic resonance; Magnetic resonance imaging; Magnetic Resonance Imaging - methods; Mathematical models; Medical sciences; Miscellaneous. Technology; Models, Theoretical; Pathology; Radio frequency; Radiodiagnosis. Nmr imagery. Nmr spectrometry; Robustness; Tissue; Performance evaluation; Image quality; Heterogeneity; Bias; Intensity; Standardization; Non parametric method; Medical imagery; Iterative method; Automatic correction; Nuclear magnetic resonance imaging; Modeling
• ISSN: 0278-0062; 1558-254X
• DOI: 10.1109/42.668698

A novel approach to correcting for intensity nonuniformity in magnetic resonance (MR) data is described that achieves high performance without requiring a model of the tissue classes present. The method has the advantage that it can be applied at an early stage in an automated data analysis, before a tissue model is available. Described as nonparametric nonuniform intensity normalization (N3), the method is independent of pulse sequence and insensitive to pathological data that might otherwise violate model assumptions. To eliminate the dependence of the field estimate on anatomy, an iterative approach is employed to estimate both the multiplicative bias field and the distribution of the true tissue intensities. The performance of this method is evaluated using both real and simulated MR data.