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Experiments with large ensembles for segmentation and classification of cervical cancer biopsy images.

, , , , , , and . SMC, page 870-875. IEEE, (2014)

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LNDb challenge on automatic lung cancer patient management., , , , , , , , , and 16 other author(s). Medical Image Anal., (2021)Experiments with large ensembles for segmentation and classification of cervical cancer biopsy images., , , , , , and . SMC, page 870-875. IEEE, (2014)An Ensemble Algorithm Framework for Automated Stereology of Cervical Cancer., , , , , , and . ICIAP (1), volume 8156 of Lecture Notes in Computer Science, page 823-832. Springer, (2013)Automatic Lung Cancer Follow-Up Recommendation with 3D Deep Learning., and . ICIAR (2), volume 12132 of Lecture Notes in Computer Science, page 406-418. Springer, (2020)Automatic quantification and classification of cervical cancer via Adaptive Nucleus Shape Modeling., , , , and . ICIP, page 2658-2662. IEEE, (2016)Iterative Deep Learning Based Unbiased Stereology with Human-in-the-Loop., , , , , and . ICMLA, page 665-670. IEEE, (2018)A New Cervical Cytology Dataset for Nucleus Detection and Image Classification (Cervix93) and Methods for Cervical Nucleus Detection., and . CoRR, (2018)A new approach to detect and segment overlapping cells in multi-layer cervical cell volume images., , , and . ISBI, page 201-204. IEEE, (2016)Adaptive Region-Based Approaches for Cellular Segmentation of Bright-Field Microscopy Images.. University of South Florida, Tampa, USA, (2017)base-search.net (ftunisfloridatam:oai:digitalcommons.usf.edu:etd-7991).