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Automatic quantification and classification of cervical cancer via Adaptive Nucleus Shape Modeling.

, , , , and . ICIP, page 2658-2662. IEEE, (2016)

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Iterative Deep Learning Based Unbiased Stereology With Human-in-the-Loop., , , , , and . CoRR, (2019)A framework for nucleus and overlapping cytoplasm segmentation in cervical cytology extended depth of field and volume images., , , and . Comput. Medical Imaging Graph., (2017)Experiments with large ensembles for segmentation and classification of cervical cancer biopsy images., , , , , , and . SMC, page 870-875. IEEE, (2014)Automatic location of microscopic focal planes for computerized stereology., , , , , , and . Medical Imaging: Computer-Aided Diagnosis, volume 7963 of SPIE Proceedings, page 79633C. SPIE, (2011)Enhancing Neonatal Pain Assessment Transparency via Explanatory Training Examples Identification., , , , and . CBMS, page 311-316. IEEE, (2023)Toward automated quantification of biological microstructures using unbiased stereology., , , , , , and . Medical Imaging: Computer-Aided Diagnosis, volume 7963 of SPIE Proceedings, page 79633G. SPIE, (2011)A new approach to detect and segment overlapping cells in multi-layer cervical cell volume images., , , and . ISBI, page 201-204. IEEE, (2016)Automatic Cell Counting using Active Deep Learning and Unbiased Stereology., , , and . SMC, page 1708-1713. IEEE, (2019)Challenges for the Repeatability of Deep Learning Models., , , and . IEEE Access, (2020)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)