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2020 – today
- 2023
[j3]Adrien Foucart
, Olivier Debeir, Christine Decaestecker:
Shortcomings and areas for improvement in digital pathology image segmentation challenges. Comput. Medical Imaging Graph. 103: 102155 (2023)- [j2]Adrien Foucart, Olivier Debeir, Christine Decaestecker:
Evaluating participating methods in image analysis challenges: Lessons from MoNuSAC 2020. Pattern Recognit. 141: 109600 (2023) - [c4]Arthur Elskens, Adrien Foucart, Egor Zindy, Olivier Debeir, Christine Decaestecker:
Assessing Local Descriptors for Feature-Based Registration of Whole-Slide Images. SIPAIM 2023: 1-4 - [c3]Adrien Foucart, Arthur Elskens, Olivier Debeir, Christine Decaestecker:
Finding the best channel for tissue segmentation in whole-slide images. SIPAIM 2023: 1-4 - 2022
- [j1]Adrien Foucart, Olivier Debeir, Christine Decaestecker:
Comments on "MoNuSAC2020: A Multi-Organ Nuclei Segmentation and Classification Challenge". IEEE Trans. Medical Imaging 41(4): 997-999 (2022)
2010 – 2019
- 2019
- [c2]Adrien Foucart, Olivier Debeir, Christine Decaestecker:
SNOW: Semi-Supervised, Noisy And/Or Weak Data For Deep Learning In Digital Pathology. ISBI 2019: 1869-1872 - 2018
- [c1]Adrien Foucart, Olivier Debeir, Christine Decaestecker:
Artifact Identification in Digital Pathology from Weak and Noisy Supervision with Deep Residual Networks. Cloudtech 2018: 1-6
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