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An enhanced random walk algorithm for delineation of head and neck cancers in PET studies

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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.

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Acknowledgments

This work was partially supported by CIPE1 (n. DM45602).

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Authors and Affiliations

  1. Institute of Molecular Bioimaging and Physiology, National Research Council (IBFM-CNR), Cefalù, PA, Italy

    Alessandro Stefano, Giorgio Russo & Maria Carla Gilardi

  2. Department of Chemical, Management, Information Technology and Mechanical Engineering, University of Palermo, Palermo, Italy

    Alessandro Stefano, Orazio Gambino, Roberto Pirrone & Edoardo Ardizzone

  3. Department of Biopathology and Medical Biotechnologies (DIBiMED), University of Palermo, Palermo, Italy

    Salvatore Vitabile

  4. Medical Physics Unit, Cannizzaro Hospital, Catania, Italy

    Giorgio Russo, Maria Gabriella Sabini & Daniele Sardina

  5. Nuclear Medicine Department, Cannizzaro Hospital, Catania, Italy

    Massimo Ippolito

Authors
  1. Alessandro Stefano
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  2. Salvatore Vitabile
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  3. Giorgio Russo
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  5. Maria Gabriella Sabini
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Correspondence to Alessandro Stefano.

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Stefano, A., Vitabile, S., Russo, G. et al. An enhanced random walk algorithm for delineation of head and neck cancers in PET studies. Med Biol Eng Comput 55, 897–908 (2017). https://doi.org/10.1007/s11517-016-1571-0

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  • DOI: https://doi.org/10.1007/s11517-016-1571-0

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