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.
Rundo, L., Militello, C., Vitabile, S., Russo, G., Pisciotta, P., Marletta, F., et al. (2016). Semi-automatic brain lesion segmentation in gamma knife treatments using an unsupervised fuzzy c-means clustering technique. In International Workshop on Neural Networks, WIRN 2015; Vietri sul Mare; Italy; 20 May 2015 through 22 May 2015 (pp.15-26). GEWERBESTRASSE 11, CHAM, CH-6330, SWITZERLAND : Springer Science and Business Media Deutschland GmbH [10.1007/978-3-319-33747-0_2].
Citazione: | Rundo, L., Militello, C., Vitabile, S., Russo, G., Pisciotta, P., Marletta, F., et al. (2016). Semi-automatic brain lesion segmentation in gamma knife treatments using an unsupervised fuzzy c-means clustering technique. In International Workshop on Neural Networks, WIRN 2015; Vietri sul Mare; Italy; 20 May 2015 through 22 May 2015 (pp.15-26). GEWERBESTRASSE 11, CHAM, CH-6330, SWITZERLAND : Springer Science and Business Media Deutschland GmbH [10.1007/978-3-319-33747-0_2]. | |
Tipo: | paper | |
Carattere della pubblicazione: | Scientifica | |
Presenza di un coautore afferente ad Istituzioni straniere: | No | |
Titolo: | Semi-automatic brain lesion segmentation in gamma knife treatments using an unsupervised fuzzy c-means clustering technique | |
Autori: | Rundo, L; Militello, C; Vitabile, S; Russo, G; Pisciotta, P; Marletta, F; Ippolito, M; D'Arrigo, C; Midiri, M; Gilardi, M | |
Autori: | ||
Data di pubblicazione: | 2016 | |
Lingua: | English | |
Nome del convegno: | International Workshop on Neural Networks, WIRN 2015 20-22 May | |
ISBN: | 9783319337463 | |
Serie: | SMART INNOVATION, SYSTEMS AND TECHNOLOGIES | |
Digital Object Identifier (DOI): | http://dx.doi.org/10.1007/978-3-319-33747-0_2 | |
Appare nelle tipologie: | 02 - Intervento a convegno |