Dan Ma1, Kecheng Liu2, Mark Griswold1
T1 and T2 quantification have been used for long time in clinical routine diagnosis. Diagnosis relies objectively on absolute T1, T2 quantification rather than subjectively on gray-scaled images. Therefore, the reliability of quantified values should be ensured for clinical diagnosis. In reality, even a slightly system performance imperfection will have big impact on quantified mapping values that may not be seen on gray scaled images. This work introduces a self-justification fitting to improve accuracy of the quantified T2 values due to system imperfections, and to predict the measurable quantification range.