Publications

List of publications

For the definitive versions of each journal/conference publication, refer to the DOI link.

A. Foucart
Comprendre et évaluer les intelligences artificielles
Séminaire donné au Skeptics in the Pub Liège (décembre 2023) et à Casa Nova (février 2024)
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A. Foucart
Intelligence artificielle: une nouvelle ère?
Séminaire donné en faculté de Droit (mars 2023)
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A. Foucart, A. Elskens, O. Debeir, C. Decaestecker
Finding the best channel for tissue segmentation in whole-slide images
Proc. 19th International Symposium on Medical Information Processing and Analysis (November 2023)
doi:10.1109/SIPAIM56729.2023.10373416 Di-fusion Download View Code
A. Elskens, A. Foucart, E. Zindy, O. Debeir, C. Decaestecker
Assessing Local Descriptors for Feature-Based Registration of Whole-Slide Images
Proc. 19th International Symposium on Medical Information Processing and Analysis (November 2023)
doi:10.1109/SIPAIM56729.2023.10373514 Di-fusion Code
A. Foucart, O. Debeir, C. Decaestecker.
Panoptic Quality should be avoided as a metric for assessing cell nuclei segmentation and classification in digital pathology
Scientific Reports 13 (8614), 2023
doi:10.1038/s41598-023-35605-7 Download View Code
A. Foucart, O. Debeir, C. Decaestecker.
Evaluating participating methods in image analysis challenges: lessons from MoNuSAC 2020
Pattern Recognition (141), 2023
doi:10.1016/j.patcog.2023.109600 Download View Code
A. Foucart, O. Debeir, C. Decaestecker.
Shortcomings and areas for improvement in digital pathology image segmentation challenges
Computerized Medical Imaging and Graphics (103), 2023
doi:10.1016/j.compmedimag.2022.102155 Download View
A. Foucart, O. Debeir, C. Decaestecker.
Comments on "Monusac2020: A Multi-Organ Nuclei Segmentation and Classification Challenge"
IEEE Trans. Medical Imaging, 2022
doi:10.1109/TMI.2022.3156023 Download View Code
A. Foucart, O. Debeir, C. Decaestecker.
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
doi:10.1117/12.2604307 Download View Code
A. Foucart, O. Debeir, C. Decaestecker.
SNOW Supervision in Digital Pathology: Managing Imperfect Annotations for Segmentation in Deep Learning.
Report, 2020
doi:10.5281/zenodo.8354443 Download View Code
Y-R. Van Eycke, A. Foucart, C. Decaestecker
Strategies to Reduce the Expert Supervision Required for Deep Learning-Based Segmentation of Histopathological Images.
Frontiers in Medicine (6), 2019
doi:10.3389/fmed.2019.00222
A. Foucart, O. Debeir, C. Decaestecker.
SNOW: Semi-Supervised, NOisy and/or Weak Data for Deep Learning in Digital Pathology.
ISBI, 2019
doi:10.1109/ISBI.2019.8759545 Download View Code
A. Foucart, O. Debeir, C. Decaestecker.
Artifact Identification in Digital Pathology from Weak and Noisy Supervision with Deep Residual Networks.
Cloud'Tech, 2018
doi:10.1109/CloudTech.2018.8713350 Download View Code