title: An enhanced random walk algorithm for delineation of head and neck cancers in PET studies.
abstract: An algorithm for delineating complex head and neck cancers in positron emission tomography (PET) images is presented in this article. An enhanced random walk (RW) algorithm with automatic seed detection is proposed and used to make the segmentation process feasible in the event of inhomogeneous lesions with bifurcations. In addition, an adaptive probability threshold and a k-means based clustering technique have been integrated in the proposed enhanced RW algorithm. The new threshold is capable of following the intensity changes between adjacent slices along the whole cancer volume, leading to an operator-independent algorithm. Validation experiments were first conducted on phantom studies: High Dice similarity coefficients, high true positive volume fractions, and low Hausdorff distance confirm the accuracy of the proposed method. Subsequently, forty head and neck lesions were segmented in order to evaluate the clinical feasibility of the proposed approach against the most common segmentation algorithms. Experimental results show that the proposed algorithm is more accurate and robust than the most common algorithms in the literature. Finally, the proposed method also shows real-time performance, addressing the physician's requirements in a radiotherapy environment.
authors.affiliation: Institute of Molecular Bioimaging and Physiology, National Research Council (IBFM-CNR), Cefalù, PA, Italy. alessandro.stefano@ibfm.cnr.it.|Department of Chemical, Management, Information Technology and Mechanical Engineering, University of Palermo, Palermo, Italy. alessandro.stefano@ibfm.cnr.it.
authors.forename: Alessandro
authors.identifier: http://orcid.org/0000-0002-7189-1731
authors.initials: A
authors.lastname: Stefano
authors.affiliation: Department of Biopathology and Medical Biotechnologies (DIBiMED), University of Palermo, Palermo, Italy.
authors.forename: Salvatore
authors.initials: S
authors.lastname: Vitabile
authors.affiliation: Institute of Molecular Bioimaging and Physiology, National Research Council (IBFM-CNR), Cefalù, PA, Italy.|Medical Physics Unit, Cannizzaro Hospital, Catania, Italy.
authors.forename: Giorgio
authors.initials: G
authors.lastname: Russo
authors.affiliation: Nuclear Medicine Department, Cannizzaro Hospital, Catania, Italy.
authors.forename: Massimo
authors.initials: M
authors.lastname: Ippolito
authors.affiliation: Medical Physics Unit, Cannizzaro Hospital, Catania, Italy.
authors.forename: Maria Gabriella
authors.initials: MG
authors.lastname: Sabini
authors.affiliation: Medical Physics Unit, Cannizzaro Hospital, Catania, Italy.
authors.forename: Daniele
authors.initials: D
authors.lastname: Sardina
authors.affiliation: Department of Chemical, Management, Information Technology and Mechanical Engineering, University of Palermo, Palermo, Italy.
authors.forename: Orazio
authors.initials: O
authors.lastname: Gambino
authors.affiliation: Department of Chemical, Management, Information Technology and Mechanical Engineering, University of Palermo, Palermo, Italy.
authors.forename: Roberto
authors.initials: R
authors.lastname: Pirrone
authors.affiliation: Department of Chemical, Management, Information Technology and Mechanical Engineering, University of Palermo, Palermo, Italy.
authors.forename: Edoardo
authors.initials: E
authors.lastname: Ardizzone
authors.affiliation: Institute of Molecular Bioimaging and Physiology, National Research Council (IBFM-CNR), Cefalù, PA, Italy.
authors.forename: Maria Carla
authors.initials: MC
authors.lastname: Gilardi
mesh_terms: D000465:Algorithms; D006258:Head and Neck Neoplasms / Q000175:diagnosis*; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods; D019047:Phantoms, Imaging; D049268:Positron-Emission Tomography / Q000379:methods*
keywords: Biological target volume; Head and neck cancer segmentation; PET imaging; Random walks