Self-Justification Fitting to Improve Reliability of Relaxometry Quantification

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.