All PDF files and HTML versions are of the preprints. For the definitive versions of each publication, refer to the DOI link.
Finding the best channel for tissue segmentation in whole-slide images
Accepted at the SIPAIM 2023 conference (November 2023)
Panoptic Quality should be avoided as a metric for assessing cell nuclei segmentation and classification in digital pathology
Scientific Reports 13 (8614), 2023
Evaluating participating methods in image analysis challenges: lessons from MoNuSAC 2020
Pattern Recognition (141), 2023
Shortcomings and areas for improvement in digital pathology image segmentation challenges
Computerized Medical Imaging and Graphics (103), 2023
Comments on "Monusac2020: A Multi-Organ Nuclei Segmentation and Classification Challenge"
IEEE Trans. Medical Imaging, 2022
Processing multi-expert annotations in digital pathology: a study of the Gleason2019 challenge.
Proc. SPIE 12088, 17th International Symposium on Medical Information Processing and Analysis, 2021
SNOW Supervision in Digital Pathology: Managing Imperfect Annotations for Segmentation in Deep Learning.
Strategies to Reduce the Expert Supervision Required for Deep Learning-Based Segmentation of Histopathological Images.
Frontiers in Medicine (6), 2019
SNOW: Semi-Supervised, NOisy and/or Weak Data for Deep Learning in Digital Pathology.
Artifact Identification in Digital Pathology from Weak and Noisy Supervision with Deep Residual Networks.