Zheng B, Chang Y H, Gur D
Department of Radiology, University of Pittsburgh, PA 15261-0001, USA.
Acad Radiol. 1995 Dec;2(12):1056-61. doi: 10.1016/s1076-6332(05)80513-6.
Two methods--single-image segmentation and bilateral-image subtraction--have been used commonly as the first stage in computer-aided detection (CAD) schemes to detect masses on digitized mammograms. In the current study, we investigated and compared the advantages and disadvantages of the two methods in achieving a high sensitivity for mass detection.
Two CAD schemes were tested. One used Gaussian filtering based on single-image segmentation, and the other used bilateral-image subtraction based on left-right image pairs to identify suspicious mass regions. A clinical database that contained 152 verified mass cases was used to compare the two approaches.
The single-image segmentation method yielded 100% sensitivity and had a somewhat higher number of initial suspicious regions. The bilateral-image subtraction method missed several true-positive regions at the initial phase. Each approach achieved more than 90% sensitivity at a false-positive rate of approximately 0.8 per image.
Optimal initial image segmentation schemes may depend on the complete detection and classification method used. Single-image segmentation methods may perform comparably with bilateral-image segmentation schemes, and these techniques appear to be more versatile and easily adaptable to future clinical CAD applications.
单图像分割和双边图像相减这两种方法通常被用作计算机辅助检测（CAD）方案的第一阶段，以在数字化乳腺X线照片上检测肿块。在本研究中，我们调查并比较了这两种方法在实现高肿块检测灵敏度方面的优缺点。
测试了两种CAD方案。一种基于单图像分割使用高斯滤波，另一种基于左右图像对使用双边图像相减来识别可疑肿块区域。使用一个包含152例经证实的肿块病例的临床数据库来比较这两种方法。
单图像分割方法的灵敏度为100%，初始可疑区域数量略多。双边图像相减方法在初始阶段遗漏了几个真阳性区域。在每张图像假阳性率约为0.8的情况下，每种方法的灵敏度均超过90%。
最佳的初始图像分割方案可能取决于所使用的完整检测和分类方法。单图像分割方法可能与双边图像分割方案表现相当，并且这些技术似乎更具通用性，更容易适应未来的临床CAD应用。
