Mammography is currently regarded as the most effective and widely used method for early detection of breast cancer, but recently its sensitivity in certain high risk cases has been less than desired. The use of Dynamic Contrast Enhanced Magnetic Resonance Imaging (DCE-MRI) has gained considerable attention in the past 10 years, especially for high risk cases, for smaller multi-focal lesions, or very sparsely distributed lesions. In this work, we present an interactive visualization system to identify, process, visualize and quantify lesions from DCE-MRI volumes. Our approach has the following key features: (1) we determine a confidence measure for each voxel, representing the probability that the voxel is part of the tumor, using a rough goodness-of-fit for the shape of the intensity-time curves, (2) our system takes advantage of low-cost, readily available 3D texture mapping hardware to produce both 2D and 3D visualizations of the segmented MRI volume in near real-time, enabling improved spatial perception of the tumor location, shape, size, distribution, and other characteristics useful in staging and treatment courses, and (3) our system permits interactive manipulation of the signal-time curves, adapts to different tumor types and morphology, thus making it a powerful tool for radiologists/physicians to rapidly assess probable malignant volumes. We illustrate the application of our system with four case studies: invasive ductal cancer, benign fibroadenoma, ductal carcinoma in situ and lobular carcinoma.