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Stacked Sparse Autoencoder (SSAE) for Nuclei Detection on Breast Cancer Histopathology Images
2016
IEEE Transactions on Medical Imaging
Automated nuclear detection is a critical step for a number of computer assisted pathology related image analysis algorithms such as for automated grading of breast cancer tissue specimens. The Nottingham Histologic Score system is highly correlated with the shape and appearance of breast cancer nuclei in histopathological images. However, automated nucleus detection is complicated by (1) the large number of nuclei and the size of high resolution digitized pathology images, and (2) the
doi:10.1109/tmi.2015.2458702
pmid:26208307
pmcid:PMC4729702
fatcat:xuz7swthcjanphpzhf7tqxcysu