Bias correction in the thoracic region is challenging due to the low proton density in the lung. Traditional retrospective bias correction techniques, such as surface fitting method and the histogram-based method, suffer from over suppression in the lung regions or increased noise in the tissue. We propose a hybrid bias correction method that combines the advantages of the surface fitting and the histogram-based methods. The hybrid method normalized the signal intensity in lung and reduced the signal variation in tissue.
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