A Novel Framework for Automated Segmentation and Labeling of Homogeneous Versus Heterogeneous Lung Tumors in [F]FDG-PET Imaging.

Purpose: Determination of intra-tumor high-uptake area using 2-deoxy-2-[F]fluoro-D-glucose ([F]FDG) positron emission tomography (PET) imaging is an important consideration for dose painting in radiation treatment applications. The aim of our study was to develop a framework towards automated segmentation and labeling of homogeneous vs. heterogeneous tumors in clinical lung [F]FDG-PET with the capability of intra-tumor high-uptake region delineation.

Combined fuzzy logic and random walker algorithm for PET image tumor delineation.

Purpose: The random walk (RW) technique serves as a powerful tool for PET tumor delineation, which typically involves significant noise and/or blurring. One challenging step is hard decision-making in pixel labeling. Fuzzy logic techniques have achieved increasing application in edge detection.