RT Journal Article
T1 Method for bias field correction of brain T1-weighted magnetic resonance images minimizing segmentation error
A1 Gispert, Juan D.
A1 Reig, Santiago
A1 Pascau González-Garzón, Javier
A1 Vaquero López, Juan José
A1 García Barreno, Pedro
A1 Desco Menéndez, Manuel
AB This work presents a new algorithm (nonuniform intensity correction; NIC) for correction of intensity inhomogeneities in T1-weighted magnetic resonance (MR) images. The bias field and a bias-free image are obtained through an iterative process that uses brain tissue segmentation. The algorithm was validated by means of realistic phantom images and a set of 24 real images. The first evaluation phase was based on a public domain phantom dataset, used previously to assess bias field correction algorithms. NIC performed similar to previously described methods in removing the bias field from phantom images, without introduction of degradation in the absence of intensity inhomogeneity. The real image dataset was used to compare the performance of this new algorithm to that of other widely used methods (N3, SPM'99, and SPM2). This dataset included both low and high bias field images from two different MR scanners of low (0.5 T) and medium (1.5 T) static fields. Using standard quality criteria for determining the goodness of the different methods, NIC achieved the best results, correcting the images of the real MR dataset, enabling its systematic use in images from both low and medium static field MR scanners. A limitation of our method is that it might fail if the bias field is so high that the initial histogram does not show bimodal distribution for white and gray matter
PB Wiley
SN 1097-0193
YR 2004
FD 2004-03
LK https://hdl.handle.net/10016/9373
UL https://hdl.handle.net/10016/9373
LA eng
DS e-Archivo
RD 29 jun. 2024