Semi-automatic brain lesion segmentation in gamma knife treatments using an unsupervised fuzzy c-means clustering technique

Massimo Midiri, Salvatore Vitabile, Maria Carla Gilardi, Giorgio Russo, Massimo Ippolito, Carmelo Militello, Pietro Pisciotta, Leonardo Rundo, Corrado D’Arrigo, Francesco Marletta

Risultato della ricerca: Chapter

6 Citazioni (Scopus)

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.
Lingua originaleEnglish
Titolo della pubblicazione ospiteAdvances in Neural Networks
Pagine15-26
Numero di pagine12
Volume54
Stato di pubblicazionePublished - 2016

Serie di pubblicazioni

NomeSMART INNOVATION, SYSTEMS AND TECHNOLOGIES

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Brain
Radiation
Planning
Radiotherapy
Magnetic resonance imaging
Surgery
Tumors
Imaging techniques
Clustering
Segmentation

All Science Journal Classification (ASJC) codes

  • Decision Sciences(all)
  • Computer Science(all)

Cita questo

Midiri, M., Vitabile, S., Gilardi, M. C., Russo, G., Ippolito, M., Militello, C., ... Marletta, F. (2016). Semi-automatic brain lesion segmentation in gamma knife treatments using an unsupervised fuzzy c-means clustering technique. In Advances in Neural Networks (Vol. 54, pagg. 15-26). (SMART INNOVATION, SYSTEMS AND TECHNOLOGIES).

Semi-automatic brain lesion segmentation in gamma knife treatments using an unsupervised fuzzy c-means clustering technique. / Midiri, Massimo; Vitabile, Salvatore; Gilardi, Maria Carla; Russo, Giorgio; Ippolito, Massimo; Militello, Carmelo; Pisciotta, Pietro; Rundo, Leonardo; D’Arrigo, Corrado; Marletta, Francesco.

Advances in Neural Networks. Vol. 54 2016. pag. 15-26 (SMART INNOVATION, SYSTEMS AND TECHNOLOGIES).

Risultato della ricerca: Chapter

Midiri, M, Vitabile, S, Gilardi, MC, Russo, G, Ippolito, M, Militello, C, Pisciotta, P, Rundo, L, D’Arrigo, C & Marletta, F 2016, Semi-automatic brain lesion segmentation in gamma knife treatments using an unsupervised fuzzy c-means clustering technique. in Advances in Neural Networks. vol. 54, SMART INNOVATION, SYSTEMS AND TECHNOLOGIES, pagg. 15-26.
Midiri M, Vitabile S, Gilardi MC, Russo G, Ippolito M, Militello C e altri. Semi-automatic brain lesion segmentation in gamma knife treatments using an unsupervised fuzzy c-means clustering technique. In Advances in Neural Networks. Vol. 54. 2016. pag. 15-26. (SMART INNOVATION, SYSTEMS AND TECHNOLOGIES).
Midiri, Massimo ; Vitabile, Salvatore ; Gilardi, Maria Carla ; Russo, Giorgio ; Ippolito, Massimo ; Militello, Carmelo ; Pisciotta, Pietro ; Rundo, Leonardo ; D’Arrigo, Corrado ; Marletta, Francesco. / Semi-automatic brain lesion segmentation in gamma knife treatments using an unsupervised fuzzy c-means clustering technique. Advances in Neural Networks. Vol. 54 2016. pagg. 15-26 (SMART INNOVATION, SYSTEMS AND TECHNOLOGIES).
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AU - Militello, Carmelo

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