Automatic segmentation of the breast and axillary region is an important preprocessing step for automatic lesion detection in breast MR and dynamic contrast-enhanced-MR studies. In this paper, we present a fully automatic procedure based on the detection of the upper border of the pectoral muscle. Compared with previous methods based on thresholding, this method is more robust to noise and field inhomogeneities. The method was quantitatively evaluated on 31 cases acquired from two centers by comparing the results with a manual segmentation. Results indicate good overall agreement within the reference segmentation (overlap=0.79±0.09, recall=0.95± 0.02, precision=0.82 ± 0.1).

A fully automatic algorithm for segmentation of the breasts in DCE-MR images / Giannini, Valentina; Vignati, Anna; Morra, Lia; Persano, Diego; Brizzi, Davide; Alessandro Carbonaro, Luca; Bert, Alberto; Sardanelli, Francesco; Regge, Daniele. - ELETTRONICO. - 2010:(2010), pp. 3146-3149. (Intervento presentato al convegno 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10 tenutosi a Buenos Aires, Argentina nel 31 Aug - 04 Sep 2010) [10.1109/IEMBS.2010.5627191].

A fully automatic algorithm for segmentation of the breasts in DCE-MR images

Valentina Giannini;Lia Morra;
2010

Abstract

Automatic segmentation of the breast and axillary region is an important preprocessing step for automatic lesion detection in breast MR and dynamic contrast-enhanced-MR studies. In this paper, we present a fully automatic procedure based on the detection of the upper border of the pectoral muscle. Compared with previous methods based on thresholding, this method is more robust to noise and field inhomogeneities. The method was quantitatively evaluated on 31 cases acquired from two centers by comparing the results with a manual segmentation. Results indicate good overall agreement within the reference segmentation (overlap=0.79±0.09, recall=0.95± 0.02, precision=0.82 ± 0.1).
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2692521