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Semi-automatic Brain Lesion Segmentation in Gamma Knife Treatments Using an Unsupervised Fuzzy C-Means Clustering Technique

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Advances in Neural Networks (WIRN 2015)

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 54))

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Abstract

MR Imaging is being increasingly used in radiation treatment planning as well as for staging and assessing tumor response. Leksell Gamma Knife® is a device for stereotactic neuro-radiosurgery to deal with inaccessible or insufficiently treated lesions with traditional surgery or radiotherapy. The target to be treated with radiation beams is currently contoured through slice-by-slice manual segmentation on MR images. This procedure is time consuming and operator-dependent. Segmentation result repeatability may be ensured only by using automatic/semi-automatic methods with the clinicians supporting the planning phase. In this paper a semi-automatic segmentation method, based on an unsupervised Fuzzy C-Means clustering technique, is proposed. The presented approach allows for the target segmentation and its volume calculation. Segmentation tests on 5 MRI series were performed, using both area-based and distance-based metrics. The following average values have been obtained: DS = 95.10, JC = 90.82, TPF = 95.86, FNF = 2.18, MAD = 0.302, MAXD = 1.260, H = 1.636.

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Acknowledgments

This work was supported by “Smart Health 2.0” MIUR project (PON 04a2_C), approved by MIUR D.D. 626/Ric and 703/Ric.

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Authors and Affiliations

  1. Istituto di Bioimmagini e Fisiologia Molecolare - Consiglio Nazionale delle Ricerche (IBFM-CNR), Cefalù (PA), Italy

    Leonardo Rundo, Carmelo Militello, Giorgio Russo, Pietro Pisciotta & Maria Carla Gilardi

  2. Dipartimento di Biopatologia e Biotecnologie Mediche (DIBIMED), Università degli Studi di Palermo, Palermo, Italy

    Salvatore Vitabile & Massimo Midiri

  3. Azienda Ospedaliera Cannizzaro, Catania, Italy

    Francesco Marletta, Massimo Ippolito & Corrado D’Arrigo

Authors
  1. Leonardo Rundo
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  2. Carmelo Militello
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  3. Salvatore Vitabile
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  4. Giorgio Russo
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  5. Pietro Pisciotta
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  6. Francesco Marletta
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  7. Massimo Ippolito
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  8. Corrado D’Arrigo
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  9. Massimo Midiri
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  10. Maria Carla Gilardi
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Corresponding author

Correspondence to Carmelo Militello .

Editor information

Editors and Affiliations

  1. Computer Science Department, University of Milano, Milano, Italy

    Simone Bassis

  2. Department of Psychology, Seconda Università di Napoli and IIASS, Caserta, Italy

    Anna Esposito

  3. Dept. of Info., Mathematics, Ele & Trans, Univ. Mediterranea of Reggio Calabria, Reggio Calabria, Italy

    Francesco Carlo Morabito

  4. Dip. Elettronica e Telecomunicazioni, Politecnico di Torino, Torino, Italy

    Eros Pasero

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Rundo, L. et al. (2016). Semi-automatic Brain Lesion Segmentation in Gamma Knife Treatments Using an Unsupervised Fuzzy C-Means Clustering Technique. In: Bassis, S., Esposito, A., Morabito, F., Pasero, E. (eds) Advances in Neural Networks. WIRN 2015. Smart Innovation, Systems and Technologies, vol 54. Springer, Cham. https://doi.org/10.1007/978-3-319-33747-0_2

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  • DOI: https://doi.org/10.1007/978-3-319-33747-0_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-33746-3

  • Online ISBN: 978-3-319-33747-0

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