Evaluation of a deep-learning segmentation model for patients with colorectal cancer liver metastases (COALA) in the radiological workflow
Developed segmentation models should be implemented in the radiological workflow. Our implemented segmentation model provides valuable lessons for future researchers. If implemented in clinical practice, our model could allow for objective radiological evaluation.
Authors
- Inez M. Verpalen (ORCID: https://orcid.org/0000-0002-3267-0637)
- Alexandra de Sitter (ORCID: https://orcid.org/0000-0003-2579-9675)
- Nina J. Wesdorp (ORCID: https://orcid.org/0000-0003-4234-5915)
- Henk A. Marquering (ORCID: https://orcid.org/0000-0002-1414-6313)
- Jaap Stoker (ORCID: https://orcid.org/0000-0002-9822-3784)
- Shira Moos
- Yung Nio
- Michiel Zeeuw (ORCID: https://orcid.org/0000-0001-7918-5404)
- Jan Hein van Waesberghe
- I. Nota
- Joost Huiskens (ORCID: https://orcid.org/0000-0002-0774-1042)
- Ruby Kemna (ORCID: https://orcid.org/0000-0003-0762-5778)
- Janneke van den Bergh
- Femke Struik
- Marnix P. M. Kop (ORCID: https://orcid.org/0000-0002-3047-7366)
- Geert Kazemier (ORCID: https://orcid.org/0000-0002-9811-3497)
- Boris V. Janssen (ORCID: https://orcid.org/0000-0001-5678-1510)
- Jakob W. Kist (ORCID: https://orcid.org/0000-0002-6122-429X)
- Jacqueline I. Bereska (ORCID: https://orcid.org/0000-0002-2491-5833)
- Lodewijk J. Wagenaar
- Jules Nelissen
- Katinka Rus
- Marius Strampel
Institutions
- Dutch Cancer Society (NL)
- Amsterdam Neuroscience (NL)
- Amsterdam University Medical Centers (NL)
- Cancer Center Amsterdam (NL)
- Vrije Universiteit Amsterdam (NL)
- University of Amsterdam (NL)
Publication Details
- Journal
- Insights into Imaging
- Published
- 2025-05-23
- DOI
- https://doi.org/10.1186/s13244-025-01984-w
- Citations
- 5
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 6.80
Funders
- KWF Kankerbestrijding
- Cancer Center Amsterdam