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

Author

Giannini, Valentina ; Vignati, Anna ; Morra, Lia ; Persano, Diego ; Brizzi, Davide ; Carbonaro, Luca ; Bert, Alberto ; Sardanelli, Francesco ; Regge, Daniele

Author_Institution

Electron. Dept., Politec. of Turin, Turin, Italy

fYear

2010

fDate

Aug. 31 2010-Sept. 4 2010

Firstpage

3146

Lastpage

3149

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).

Keywords

biomedical MRI; image segmentation; mammography; medical image processing; automatic image segmentation; automatic lesion detection; axillary region; breast MR imaging; dynamic contrast-enhanced-MR imaging; field inhomogeneities; image noise; pectoral muscle; thresholding; Breast; Coils; Image segmentation; Lesions; Manuals; Muscles; Pixel; Algorithms; Artificial Intelligence; Breast; Contrast Media; Female; Humans; Image Enhancement; Image Interpretation, Computer-Assisted; Magnetic Resonance Imaging; Pattern Recognition, Automated; Reproducibility of Results; Sensitivity and Specificity;

fLanguage

English

Publisher

ieee

Conference_Titel

Engineering in Medicine and Biology Society (EMBC), 2010 Annual International Conference of the IEEE

Conference_Location

Buenos Aires

ISSN

1557-170X

Print_ISBN

978-1-4244-4123-5

Type

conf

DOI

10.1109/IEMBS.2010.5627191

Filename

5627191