Methodological considerations for evaluating deep learning segmentation models in digital pathology whole-slide images.

Arab A, Garcia V, Kahaki S, van Rijthoven M, Salgado R, Gallas BD, Petrick N, Ciompi F, Chen W

DOI: 10.1117/1.jmi.13.3.037501
Published: 2026 May
Container: Journal of medical imaging (Bellingham, Wash.)
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.1117/1.jmi.13.3.037501,
  title = {Methodological considerations for evaluating deep learning segmentation models in digital pathology whole-slide images.},
  author = {Arab A and Garcia V and Kahaki S and van Rijthoven M and Salgado R and Gallas BD and Petrick N and Ciompi F and Chen W},
  year = {2026},
  journal = {Journal of medical imaging (Bellingham, Wash.)},
  doi = {10.1117/1.jmi.13.3.037501},
  url = {https://doi.org/10.1117/1.jmi.13.3.037501}
}

RIS

TY  - JOUR
TI  - Methodological considerations for evaluating deep learning segmentation models in digital pathology whole-slide images.
AU  - Arab A
AU  - Garcia V
AU  - Kahaki S
AU  - van Rijthoven M
AU  - Salgado R
AU  - Gallas BD
AU  - Petrick N
AU  - Ciompi F
AU  - Chen W
PY  - 2026
JO  - Journal of medical imaging (Bellingham, Wash.)
DO  - 10.1117/1.jmi.13.3.037501
UR  - https://doi.org/10.1117/1.jmi.13.3.037501
ER  -

APA

A, A., V, G., S, K., M, V. R., R, S., BD, G., N, P., F, C., & W, C. (2026). Methodological considerations for evaluating deep learning segmentation models in digital pathology whole-slide images.. Journal of medical imaging (Bellingham, Wash.). https://doi.org/10.1117/1.jmi.13.3.037501

Source records

pubmed · retrieved 2026-09-25T07:01:43.974Z