A high-precision hierarchical registration approach for stain- and scanner-independent colocalization on whole slide images in histopathology
This algorithm is designed exclusively to compute point cloud transformations within Whole Slide Images, achieving a high accuracy at the expense of computation time. Consequently, it should be considered a highly specialized solution tailored to a specific subset of the registration problems occurring in digital pathology.
Authors
- Tom Bisson (ORCID: https://orcid.org/0000-0002-7743-0792)
- Peter Boor (ORCID: https://orcid.org/0000-0001-9921-4284)
- Tim‐Rasmus Kiehl (ORCID: https://orcid.org/0000-0003-0616-7082)
- Peter Hufnagl (ORCID: https://orcid.org/0000-0001-6810-586X)
- Norman Zerbe (ORCID: https://orcid.org/0000-0002-0314-3037)
- Michael Franz (ORCID: https://orcid.org/0000-0003-0112-709X)
Institutions
- Humboldt-Universität zu Berlin (DE)
- Centre for East European and International Studies (DE)
- Berlin Institute of Health at Charité - Universitätsmedizin Berlin (DE)
- RWTH Aachen University (DE)
Publication Details
- Journal
- Health Information Science and Systems
- Published
- 2025-05-23
- DOI
- https://doi.org/10.1007/s13755-025-00353-7
- Citations
- 1
- Primary Topic
- AI in cancer detection
- Type
- article
- Field-Weighted Citation Impact
- 2.48
Funders
- Bundesministerium für Bildung und Forschung
- Charité – Universitätsmedizin Berlin