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Detection of the nipple in 3D automated breast ultrasound using coronal slab-average-projection and cumulative probability map

机译:使用冠状板平均投影和累积概率图检测3D自动乳房超声中的乳头

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We propose an automatic method for nipple detection on 3D automated breast ultrasound (3D ABUS) images using coronal slab-average-projection and cumulative probability map. First, to identify coronal images that appeared remarkable distinction between nipple-areola region and skin, skewness of each coronal image is measured and the negatively skewed images are selected. Then, coronal slab-average-projection image is reformatted from selected images. Second, to localize nipple-areola region, elliptical ROI covering nipple-areola region is detected using Hough ellipse transform in coronal slab-average-projection image. Finally, to separate the nipple from areola region, 3D Otsu's thresholding is applied to the elliptical ROI and cumulative probability map in the elliptical ROI is generated by assigning high probability to low intensity region. False detected small components are eliminated using morphological opening and the center point of detected nipple region is calculated. Experimental results show that our method provides 94.4% nipple detection rate.
机译:我们提出了一种自动方法,使用冠状板平均投影和累积概率图对3D自动乳房超声(3D ABUS)图像进行乳头检测。首先,为了识别在乳头乳晕区域和皮肤之间出现明显区别的冠状图像,测量每个冠状图像的偏斜度,然后选择负偏斜图像。然后,从所选图像中重新格式化冠状板平均投影图像。其次,为了定位乳头-乳晕区域,使用霍夫椭圆变换在冠状板平均投影图像中检测覆盖乳头-乳晕区域的椭圆ROI。最后,为了将乳头与乳晕区域分开,将3D Otsu阈值应用于椭圆ROI,并通过将高概率分配给低强度区域来生成椭圆ROI中的累积概率图。使用形态学开口消除错误的检测到的小成分,并计算出检测到的乳头区域的中心点。实验结果表明,我们的方法提供了94.4%的乳头检测率。

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