Sanjay-Gopal S, Chan H P, Wilson T, Helvie M, Petrick N, Sahiner B
Department of Radiology, University of Michigan, Ann Arbor 48109-0030, USA.
Med Phys. 1999 Dec;26(12):2669-79. doi: 10.1118/1.598806.
Analysis of interval change is a useful technique for detection of abnormalities in mammographic interpretation. Interval change analysis is routinely used by radiologists and its importance is well-established in clinical practice. As a first step to develop a computerized method for interval change analysis on mammograms, we are developing an automated regional registration technique to identify corresponding lesions on temporal pairs of mammograms. In this technique, the breast is first segmented from the background on the current and previous mammograms. The breast edges are then aligned using a global alignment procedure based on the mutual information between the breast regions in the two images. Using the nipple location and the breast centroid estimated independently on both mammograms, a polar coordinate system is defined for each image. The polar coordinate of the centroid of a lesion detected on the most recent mammogram is used to obtain an initial estimate of its location on the previous mammogram and to define a fan-shaped search region. A search for a matching structure to the lesion is then performed in the fan-shaped region on the previous mammogram to obtain a final estimate of its location. In this study, a quantitative evaluation of registration accuracy has been performed with a data set of 74 temporal pairs of mammograms and ground-truth correspondence information provided by an experienced radiologist. The most recent mammogram of each temporal pair exhibited a biopsy-proven mass. We have investigated the usefulness of correlation and mutual information as search criteria for determining corresponding regions on mammograms for the biopsy-proven masses. In 85% of the cases (63/74 temporal pairs) the region on the previous mammogram that corresponded to the mass on the current mammogram was correctly identified. The region centroid identified by the registration technique had an average distance of 2.8+/-1.9 mm from the centroid of the radiologist-identified region. These results indicate that our new registration technique may be useful for establishing correspondence between structures on current and previous mammograms. Once such a correspondence is established an interval change analysis could be performed to aid in both detection as well as classification of abnormal breast densities.
间期变化分析是乳腺钼靶影像解读中用于检测异常的一项有用技术。放射科医生经常使用间期变化分析，其重要性在临床实践中已得到充分确立。作为开发乳腺钼靶间期变化分析计算机化方法的第一步，我们正在研发一种自动区域配准技术，以识别乳腺钼靶影像时间序列对中的相应病变。在该技术中，首先从当前和先前的乳腺钼靶影像中分割出乳房。然后基于两幅图像中乳房区域之间的互信息，使用全局配准程序对齐乳房边缘。利用在两幅乳腺钼靶影像上独立估计的乳头位置和乳房质心，为每幅图像定义一个极坐标系。在最新乳腺钼靶影像上检测到的病变质心的极坐标用于获取其在先前乳腺钼靶影像上位置的初始估计，并定义一个扇形搜索区域。然后在先前乳腺钼靶影像的扇形区域中搜索与病变匹配的结构，以获得其位置的最终估计。在本研究中，利用由经验丰富的放射科医生提供的74对乳腺钼靶影像时间序列对数据集和真实对应信息，对配准准确性进行了定量评估。每对时间序列对中的最新乳腺钼靶影像显示有经活检证实的肿块。我们研究了相关性和互信息作为搜索标准在确定经活检证实肿块的乳腺钼靶影像上相应区域的有用性。在85%的病例（63/74对时间序列对）中，正确识别出先前乳腺钼靶影像上与当前乳腺钼靶影像上肿块相对应的区域。配准技术识别出的区域质心与放射科医生识别区域的质心平均距离为2.8±1.9毫米。这些结果表明，我们的新配准技术可能有助于建立当前和先前乳腺钼靶影像上结构之间的对应关系。一旦建立了这种对应关系，就可以进行间期变化分析，以辅助异常乳腺密度的检测和分类。
