Yin F F, Giger M L, Doi K, Vyborny C J, Schmidt R A
Kurt Rossmann Laboratories for Radiologic Image Research, Department of Radiology, University of Chicago, Illinois 60637.
Med Phys. 1994 Mar;21(3):445-52. doi: 10.1118/1.597307.
An automated technique for the alignment of right and left breast images has been developed for use in the computerized analysis of bilateral breast images. In this technique, the breast region is first identified in each digital mammogram by use of histogram analysis and morphological filtering operations. The anterior portions of the tracked breast border and computer-identified nipple positions are selected as landmarks for use in image registration. The paired right and left breast images, either from mediolateral oblique or craniocaudal views, are then registered relative to each other by use of a least-squares matching method. This automated alignment technique has been applied to our computerized detection scheme that employs a nonlinear bilateral-subtraction method for the initial identification of possible masses. The effectiveness of using bilateral subtraction in identifying asymmetries between corresponding right and left breast images is examined by comparing detection performances obtained with various computer-simulated misalignments of 40 pairs of clinical mammograms. Based on free-response receiver operating characteristic and regression analyses, the detection performance obtained with the automated alignment technique was found to be higher than that obtained with simulated misalignments. Detection performance decreased gradually as the amount of simulated misalignment increased. These results indicate that automatic alignment of breast images is possible and that mass-detection performance appears to improve with the inclusion of asymmetric anatomic information but is not sensitive to slight misalignment.
已开发出一种用于对左右乳房图像进行对齐的自动化技术，用于双侧乳房图像的计算机分析。在该技术中，首先通过直方图分析和形态学滤波操作在每个数字化乳腺造影片中识别出乳房区域。将跟踪的乳房边界的前部和计算机识别的乳头位置选作图像配准的地标。然后，使用最小二乘法匹配方法将来自内外斜位或头尾位视图的配对左右乳房图像相互配准。这种自动化对齐技术已应用于我们的计算机检测方案，该方案采用非线性双边减法方法来初步识别可能的肿块。通过比较40对临床乳腺造影片的各种计算机模拟错位所获得的检测性能，研究了使用双边减法识别相应左右乳房图像之间不对称性的有效性。基于自由响应接收器操作特性和回归分析，发现使用自动化对齐技术获得的检测性能高于模拟错位所获得的性能。随着模拟错位量的增加，检测性能逐渐下降。这些结果表明乳房图像的自动对齐是可行的，并且包含不对称解剖信息似乎可以提高肿块检测性能，但对轻微错位不敏感。
