Spatial encoding and growth-related change of sheep lung radiomic features
Overall, our results indicate that although sheep lung radiomic features are influenced by the lung segment of origin, their variation over time is largely consistent throughout the lung. Such influence should be borne in mind when interpreting radiomic features and their changes over time.
Authors
- Mark Gray (ORCID: https://orcid.org/0000-0003-2035-1425)
- Ziyuan Chang (ORCID: https://orcid.org/0009-0001-8819-5038)
- Calum Gray (ORCID: https://orcid.org/0000-0002-2816-4707)
- David J. Griffiths (ORCID: https://orcid.org/0000-0001-9160-0770)
- Chris Cousens (ORCID: https://orcid.org/0000-0003-3995-5472)
- Chad E. Eckert (ORCID: https://orcid.org/0000-0001-7674-4952)
- James Meehan (ORCID: https://orcid.org/0000-0001-7265-0481)
- David Collie (ORCID: https://orcid.org/0000-0001-9313-8137)
- Tom MacGillivray (ORCID: https://orcid.org/0000-0001-5120-0086)
- Helen Brown
- Nicole Storer
- Steven H. Wright
Institutions
- Johnson & Johnson (United States) (US)
- Roslin Institute (GB)
- Moredun Research Institute (GB)
- The Queen's Medical Research Institute (GB)
- University of Edinburgh (GB)
Publication Details
- Journal
- Frontiers in Veterinary Science
- Published
- 2025-02-26
- DOI
- https://doi.org/10.3389/fvets.2025.1495278
- Citations
- 2
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 2.72
Funders
- Biotechnology and Biological Sciences Research Council