Gliomas are invasive, fatal brain tumors that can be detected using magnetic resonance imaging (MRI). However, MRI does not reveal the entire size of tumor. By using a mathematical model developed by Kristin R. Swanson and colleagues, glioma growth can be quantified from the diffusion rate of the tumors cells, the net proliferation rate, and the carrying capacity of the tissue. These parameters are unique to each patient and can be determined by measuring the tumor volume from different MRI modalities as they change over time. Our lab collects data from patients consented to our study and records information about what treatments a given patient receives, since this can affect how the image appears. In my role as a member of the measurement team, I examine patient images to determine the extent of tumor burden on a given date. To obtain these measurements, I use Calcmri, a MATLAB program developed by our lab. Depending on the modality, enhancement on MRI slices can indicate tumor volume as well as other fluids. Calcmri can adjust the intensity threshold at which MRI enhancement will appear, which allows me to isolate the tumor and specify a region for the program to measure. I measure a series of two-dimensional cross section images in order to calculate a combined into 3-dimensional volume. These measurements are used to model the growth of the tumor, “in silico”. Our lab uses information from these models to discover clinical applications, such as to suggest more accurate treatment dosages and to predict life expectancy, which follows an overall goal to better capture the extent and invasion of tumor burden than what appears on MRI.