1. Demir, C., Yener, B.: Automated cancer diagnosis based on histopathological images: a systematic survey. Technical Report 05-09, Rensselaer Polytechnique Institute (2005)
2. Basavanhally, A., Ganesan, S., Agner, S., Monaco, J., Feldman, M., Tomaszewski, J., Bhanot, G., Madabhushi, A.: Computerized image-based detection and grading of lymphocytic infiltration in her2+ breast cancer histopathology. IEEE Transactions on Biomedical Engineering 57(3), 642–653 (2010)
3. Basavanhally, A., Agner, S., Alexe, G., Ganesan, G.B.S., Madabhushi, A.: Manifold learning with graph-based features for identifying extent of lymphocytic infiltration from high grade breast cancer histology. In: Workshop on Microscopic Image Analysis with Applications in Biology (in conjunction with MICCAI) (2008)
4. Fatakdawala, H., Basavanhally, A., Xu, J., Bhanot, G., Ganesan, S., Feldman, M., Tomaszewski, J., Madabhushi, A.: Expectation maximization driven geodesic active contour with overlap resolution (EMaGACOR): Application to lymphocyte segmentation on breast cancer histopathology. IEEE Transactions on Biomedical Engineering (to appear, 2010)
5. Smets, P., Kennes, R.: The Transferable Belief Model. Artificial Intelligence 66(2), 191–234 (1994)