Title :
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
fDate :
Aug. 31 2010-Sept. 4 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).
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;
Conference_Titel :
Engineering in Medicine and Biology Society (EMBC), 2010 Annual International Conference of the IEEE
Conference_Location :
Buenos Aires
Print_ISBN :
978-1-4244-4123-5
DOI :
10.1109/IEMBS.2010.5627191