Méndez A J, Tahoces P G, Lado M J, Souto M, Correa J L, Vidal J J
Department of Radiology, University of Santiago de Compostela, Complejo Hospitalario Universitario de Santiago de Compostela, Spain.
Comput Methods Programs Biomed. 1996 May;49(3):253-62. doi: 10.1016/0169-2607(96)01724-5.
Advances in the area of computerized image analysis applied to mammography may have very important practical applications in automatically detecting asymmetries (masses, architectural distortions, etc.) between the two breasts. We have developed a fully automatic technique to detect the breast border and the nipple, this being a necessary prerequisite for further image analysis. To detect the breast border, an algorithm that computes the gradient of gray levels was applied. To detect the nipple, three algorithms were compared (maximum height of the breast border, maximum gradient, and maximum second derivative of the gray levels across the median-top section of the breast). A combined method was also designed. The algorithms were tested on 156 digitized mammograms. The breast segmentation results were evaluated by two expert radiologists and one physicist. In 89% of the mammograms, the computed border was in close agreement with the radiologist's estimated border. Segmentation results were acceptable to be used in computer-aided diagnostic schemes. The mean distance between the position of the nipple indicated by two radiologists by consensus and the position calculated by the computer was 6 mm.
应用于乳腺X线摄影的计算机图像分析领域的进展在自动检测双侧乳房之间的不对称情况（肿块、结构扭曲等）方面可能具有非常重要的实际应用。我们已经开发出一种全自动技术来检测乳房边界和乳头，这是进一步图像分析的必要前提。为了检测乳房边界，应用了一种计算灰度梯度的算法。为了检测乳头，对三种算法进行了比较（乳房边界的最大高度、最大梯度以及横跨乳房中间顶部区域的灰度的最大二阶导数）。还设计了一种组合方法。这些算法在156张数字化乳腺X线照片上进行了测试。乳房分割结果由两位放射科专家和一位物理学家进行评估。在89%的乳腺X线照片中，计算出的边界与放射科医生估计的边界高度吻合。分割结果可用于计算机辅助诊断方案。两位放射科专家经协商确定的乳头位置与计算机计算出的位置之间的平均距离为6毫米。
