The current work is a case study with a segmentation and quantification of a lymphoma volume present in three dimensional (3D) images taken with positron emission tomography and fused with multilayer computerized tomography (PET-CT) belonging to a pediatric patient diagnosed with Non-Hodgkin's Lymphoma (NHL). A NHL tumor was manually delineated, and delineated with a semi-automated methodology. This last is divided in three stages: pre-processing, volumetric segmentation, and volume quantification. The pre-processing stage is based on the application of a filtering process aimed at increasing the quality of the information present in the 3D images. In order to achieve the image quality improvement a technique called Global Similarity Enhancement (GSE) is used, which is associated with the use of non-linear filtered algorithms. For the volumetric segmentation stage, a variational technique based on same level sets is used. The quantitative analysis of the segmented volumes allows for the delimitation of a NHL and the calculation of its BTV, but the semi-automated methodology must be calibrated with phantom simulated volumes, and compared with manual delineations, but that is left for subsequent studies.