Harnessing Advanced Machine Learning Techniques for Microscopic Vessel Segmentation in Pulmonary Fibrosis Using Novel Hierarchical Phase-Contrast Tomography Images
Further quantitative research is required to better assess the generalizability of these findings, though they show promising first steps toward leveraging this novel data to tackle fibrotic lung disease.
Authors
- Joseph Jacob (ORCID: https://orcid.org/0000-0002-8054-2293)
- Yufei Wang (ORCID: https://orcid.org/0009-0001-4553-081X)
- Pardeep Vasudev
- Paul Tafforeau (ORCID: https://orcid.org/0000-0002-5962-1683)
- Claire Walsh (ORCID: https://orcid.org/0000-0003-3769-3392)
- Robert Chapman (ORCID: https://orcid.org/0000-0003-0093-1086)
- Moucheng Xu (ORCID: https://orcid.org/0000-0003-3368-9871)
- Christopher Werlein (ORCID: https://orcid.org/0000-0002-7694-4257)
- Peter Lee (ORCID: https://orcid.org/0000-0002-3898-8881)
- Hannah Coleman
- Shahab Aslani (ORCID: https://orcid.org/0009-0007-6298-7874)
Institutions
- European Synchrotron Radiation Facility (FR)
- Medizinische Hochschule Hannover (DE)
- Farr Institute (GB)
- University College London (GB)
Publication Details
- Journal
- Methods of Information in Medicine
- Published
- 2024-09-01
- DOI
- https://doi.org/10.1055/a-2540-8166
- Citations
- 2
- Primary Topic
- Photoacoustic and Ultrasonic Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.37
Funders
- Wellcome Trust