Computerized Detection of Masses in Digitized Mammograms Using Single-Image Segmentation and a Multilayer Topographic Feature Analysis Bin Zheng, PhD, Yuan-Hsiang Chang, MS, David Gur, ScD Rationale and Objectives. We developed and evaluated a computer- aided detection (CAD) scheme for masses in digitized mammograms. Methods. A multistep CAD scheme was developed and tested. The method uses a technique of single-image segmentation with Gaussian bandpass filtering to yield a high sensitivity for mass detection. A rule- based multilayer topographic feature analysis method is then used to clas- sify suspected regions. A set of 260 cases, including 162 verified masses, was divided into two subsets; one set was used to set the rule-based classi- fication and one was used to test the performance of the scheme. Results. In a preliminary clinical study, the implemented detection scheme yielded 98% sensitivity with a false-positive detection rate of less than one false-positive region per image. Conclusion. Singleqmage segmentation methods seem to have high sensitivity in selecting true-positive mass regions in the first stage of a CAD scheme. A multilayer topographic image feature analysis method in the second stage of a CAD scheme has the potential to significantly reduce the false-positive detection rate. Key Words. Mammography; computer-aided detection; digital mammo- grams; mass detection; medical image processing. From the Department of Radiology, University of Pittsburgh, Pittsburgh, PA. Address reprint requests to B. Zheng, PhD, Depart- ment of Radiology, A449 Scaife Hall, University of Pittsburgh, 3550 Terrace St., Pittsburgh, PA 15261- 0001. Received April 13, 1995, and accepted for publica- tion after revision July 21, 1995. Acad Radio11995;2:959-966 © 1995, Association of University Radiologists B reast cancer is one of the leading causes of death in women over the age of 40 [1]. There is ample evidence that early detection plays an important role in reducing breast cancer morbidity and mortality [2, 3]. Many methods have been investigated to improve the early detection of breast cancer, but mammography has proved to be the most cost-effective means to provide useful information about the presence of abnormal tis- sues, such as cancer, in the breast [4]. Because of the difficulty in interpreting mammograms, multiple readings of a single examination are often desirable to increase the reliability of a diagnosis [5]. Furthermore, because of the subtlety of certain breast abnor- malities and the complexity of the reading task, mammographers may poten- 959