Point‐cloud segmentation with in‐silico data augmentation for prostate cancer treatment
Our proposed method demonstrates favorable performance in the segmentation of X-ray CT data. Results confirmed that the point-cloud-model is faster than voxel-based segmentation algorithms while achieving comparable or better segmentation results. The segmentation approach can be integrated into ART workflow, ultimately reducing the workload of clinicians and radiologists.
Authors
- Angela Di Fulvio (ORCID: https://orcid.org/0000-0001-5244-7179)
- Gregory M. Hermann (ORCID: https://orcid.org/0000-0003-3386-8546)
- Massimiliano Salvatori
- Jianxin Zhou (ORCID: https://orcid.org/0000-0002-6600-9564)
- Kadishe Fejza
Institutions
- University of Illinois Urbana-Champaign (US)
- OSF HealthCare (US)
- National Research Council (IT)
Publication Details
- Journal
- Medical Physics
- Published
- 2025-04-03
- DOI
- https://doi.org/10.1002/mp.17815
- Primary Topic
- Advanced Radiotherapy Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00