Keywords: Signal Modeling, SusceptibilityAbdominal Quantitative Susceptibility Mapping (QSM) involves a series of additional challenges compared with brain QSM, mainly because of the presence of undesired contributions related to fat and gasses. Previously, we proposed a QSM phantom with fat contributions, which emulated different susceptibility scenarios in the abdominal region. In this work, we present an improved version which now considers additional features including a variable multi-peak fat model, variable R2* and background field features. Simulation experiments show how these new components produce of different effects, like increased signal decay in specific tissues, 1st and 2nd kind chemical shift artifacts and water/fat swaps in graph cuts reconstructions.
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