Magnetic Resonance Fingerprinting (MRF) is a platform for obtaining multiple simultaneous quantitative measurements of MR properties (1), and has been used for direct calculation of T1 and T2 (1,2,3) maps as well as tissue fraction maps for gray matter (GM), white matter (WM), and CSF (4,5). Another possibility is that these coregistered maps can be used to produce single images in which color is used to encode the multidimensional quantitative information, to ease visual interpretation. In this study, a color conversion is derived, in which normal T1 and T2 values in GM, WM and CSF are mapped to grayscale values, and areas where the relaxation parameters vary significantly from normal appear colored. This algorithm was used to generate colored images in both normal volunteers and patients with brain tumors, and the method was found to be reproducible and sensitive to tissue changes. The combination of the MRF sequence with the color display shown here has the potential to simplify both the acquisition and interpretation of clinical brain exams.Experiments were performed on a 3T Siemens Verio and Skyra (Siemens, Erlangen, Germany) on a healthy volunteers and brain tumor patients (n=6). Using previously published MRF acquisition and reconstruction methods (1,3), T1 and T2 maps were generated by matching MRF time courses to a dictionary of signals that encompasses a large range of parameter values. Tissue fractions of GM, WM, and CSF were computed using a 3-component decomposition as previously described in (4,5). For generation of the hybrid color images, each property map was transformed to values between 0 and 1. The respective parameter values found in WM, GM and CSF were then mapped to predefined target intensities of 0.7, 0.5 and 0.1, respectively, using a cubic interpolation, thus creating an image with a T1-weighted appearance. While multiple combinations of parameters can be visualized with this method, two initial results are shown here. For Figure 1, an inversion recovery T1-weighted intensity map was used for the green color component, T2-weighted intensity map was used for blue, while the average intensity of all the IR and T2 parameters was assigned to the red color channel. For Figure 2, green and blue channels were similar to Figure 1, but a weighted average of the WM and GM fraction maps was assigned to the red color channel. Example quantitative T1 and T2 maps and a hybrid color image from a normal volunteer are shown in Figure 1. It can be seen that normal brain tissue appears similar to a traditional T1- weighted image. However, blood vessels appear red and the putamen appears slightly blue, demonstrating the desired color behavior in tissues that do not have the reference GM, WM or CSF relaxation rates. Figure 2 shows a color image of a patient with a glioblastoma (GBM) using the second combination of factors. In this example, the lesion appears in bright purple and red shades, and is obvious in comparison to healthy tissues. This work demonstrates a potential method for the calculation of color images based on T1, T2 and tissue fraction maps. The goal is to obtain images in which brain tissue with normal relaxation appears nearly in grayscale, while any deviation from normal results in a residual color. These maps have the potential to simplify the interpretation of clinical brain MR, since information about three of the most relevant parameters are presented in a single, easy to interpret view. This type of display is particularly useful in combination with MRF, since the impact of misregistration due to interscan motion and differences in slice profiles between maps is eliminated. Further optimization and extensive testing in patients will be necessary to determine robustness in a wide variety of clinical settings. Other schemes to map normal tissue are possible, but the concept of mapping normal tissue to greyscale while channeling pathology to color could provide potentially clinically relevant information and easy interpretation of quantitative maps.