A Retrospective, Fully Automated and Fast Method for Intensity Inhomogeneity Correction in 7T MRI

Sven Jaeschke¹, ², Robin Martin Heidemann², Aleksandar Petrovic²

Ultra high field (UHF) MRI offers improved image contrast and higher SNR enabling isotropic, high-resolution in vivo anatomical imaging. However, image quality is affected by bias fields, which can be a hindrance for tissue segmentation or classification. In this study, we propose a novel, fast and fully automated image inhomogeneity correction method, which is well suited for UHF applications. In comparison to former methods, we employ a bounded Nelder-Mead simplex optimizer and use a joint intensity-gradient histogram to calculate entropy.