Giannini Valentina, Vignati Anna, Morra Lia, Persano Diego, Brizzi Davide, Carbonaro Luca, Bert Alberto, Sardanelli Francesco, Regge Daniele
Politecnico of Turin, Electronics Department, Italy.
Annu Int Conf IEEE Eng Med Biol Soc. 2010;2010:3146-9. doi: 10.1109/IEMBS.2010.5627191.
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).
乳房和腋窝区域的自动分割是乳腺磁共振成像(MR)和动态对比增强磁共振成像(DCE-MR)研究中自动病变检测的重要预处理步骤。在本文中,我们提出了一种基于胸肌上边界检测的全自动方法。与以往基于阈值处理的方法相比,该方法对噪声和场不均匀性具有更强的鲁棒性。通过将结果与手动分割进行比较,在从两个中心获取的31例病例上对该方法进行了定量评估。结果表明,在参考分割中总体一致性良好(重叠率=0.79±0.09,召回率=0.95±0.02,精确率=0.82±0.1)。