Real-time three-dimensional (3-D) reconstruction of epithelial structures in human mammary gland tissue blocks mapped with selected markers would be an extremely helpful tool for diagnosing breast cancer and planning treatment. Besides its clear clinical application, this tool could also shed a great deal of light on the molecular basis of the initiation and progression of breast cancer. We present a framework for real-time segmentation of epithelial structures in two-dimensional (2-D) images of sections of normal and neoplastic mammary gland tissue blocks. Complete 3-D rendering of the tissue can then be done by surface rendering of the structures detected in consecutive sections of the blocks. Paraffin-embedded or frozen tissue blocks are first sliced and sections are stained with hematoxylin and eosin. The sections are then imaged using conventional bright-field microscopy and their background corrected using a phantom image. We then use the fast-marching algorithm to roughly extract the contours of the different morphological structures in the images. The result is then refined with the level-set method, which converges to an accurate (subpixel) solution for the segmentation problem. Finally, our system stacks together the 2-D results obtained in order to reconstruct a 3-D representation of the entire tissue block under study. Our method is illustrated with results from the segmentation of human and mouse mammary gland tissue samples.
In this paper we present a scheme for real time segmentation of histological structures in microscopic images of normal and neoplastic mammary gland sections. Paraffin embedded or frozen tissue blocks are sliced, and sections are stained with hematoxylin and eosin (H&E). The sections are then imaged using conventional bright field microscopy. The background of the images is corrected by arithmetic manipulation using a "phantom." Then we use the fast marching method with a speed function that depends on the brightness gradient of the image to obtain a preliminary approximation to the boundaries of the structures of interest within a region of interest (ROI) of the entire section manually selected by the user. We use the result of the fast marching method as the initial condition for the level set motion equation. We run this last method for a few steps and obtain the final result of the segmentation. These results can be connected from section to section to build a three-dimensional reconstruction of the entire tissue block that we are studying.