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One of the goals of the National Cancer Institute (NCI) to reach more than 80% of eligible women in mammography screening by the year 2000 yet remains as a challenge. In fact, a recent medical report reveals that while other types of cancer are experiencing negative growth, breast cancer has been the only one with a positive growth rate over the last few years. This is primarily due to the fact that 1) examination process is a complex and lengthy one and 2) it is not available to the majority of women who live in remote sites. Currently for mammography screening, women have to go to doctors or cancer centers/hospitals annually while high-risk patients may have to visit more often. One way to resolve these problems is by the use of advanced networking technologies and signal processing algorithms. On one hand, software modules can help detect, with high precision, true negatives (TN), while marking true positives (TP) for further investigation. Unavoidably, in this process some false negatives (FN) will be generated that are potentially life threatening; however, inclusion of the detection software improves the TP detection and, hence, reduces FNs drastically. Since TNs are the majority of examinations on a randomly selected population, this first step reduces the load on radiologists by a tremendous amount. On the other hand, high-speed networking equipment can accelerate the required clinic-lab connection and make detection, segmentation, and image enhancement algorithms readily available to the radiologists. This will bring the breast cancer care, caregiver, and the facilities to the patients and expand diagnostics and treatment to the remote sites. This research describes asynchronous transfer mode telemammography network (ATMTN) architecture for real-time, online screening, detection and diagnosis of breast cancer. ATMTN is a unique high-speed network integrated with automatic robust computer-assisted diagnosis-detection/digital signal processing (CAD/DSP) metho- - ds for mass detection, region of interest (ROI) compression algorithms using Digital Imaging and Communications in Medicine (DICOM) 3.0 medical image standard. While ATMTN has the advantage of higher penetration into the women for cancer screening, it provides the diagnosis with higher efficiency, better accuracy and potentially lower cost. This paper presents the development of the infrastructure and algorithm design for ATMTN-based telemammography. The research goals involved: 1) networking stations for telemammography to demonstrate, evaluate, and validate technologies and methods for delivering mammography screening services via high-speed (155 MB/s) links, performing real-time network-transmitted, high-resolution mammograms for immediate diagnosis as a "second opinion" strategy; 2) development of object-oriented compression methods for storage, retrieval and transmission of mammograms; 3) inclusion and optimization of detection algorithms for identification of normal images in different resolutions to increase the speed and effectiveness of telemammography as a "second opinion" strategy; 4) resolving the compatibility issues between images from different equipment (DICOM standards); and 5) optimization of an integrated ATMTN with adaptive CAD/DSP methods that are robust for large image databases and input sources.