Computer-Aided Detection (CADe) of Small Metastatic Prostate Cancer Lesions on 3D PSMA PET Volumes Using Multi-Angle Maximum Intensity Projections
Our fully automated CADe tool shows promise in assisting physicians as a "second reader" for detecting small metastatic BCR PCa lesions on PSMA-PET images. By leveraging the strength and computational efficiency of 2D models while preserving 3D spatial information of the PSMA-PET volume, the proposed approach has the potential to improve detectability and reduce workload in cancer diagnosis and management.
Authors
- Arman Rahmim (ORCID: https://orcid.org/0000-0002-9980-2403)
- Rahul Dodhia (ORCID: https://orcid.org/0000-0003-3812-3906)
- Felipe Oviedo (ORCID: https://orcid.org/0000-0001-9480-6539)
- Juan Lavista Ferres (ORCID: https://orcid.org/0000-0002-9654-3178)
- William B. Weeks (ORCID: https://orcid.org/0000-0002-9918-1360)
- Ghasemali Divband (ORCID: https://orcid.org/0000-0001-6011-8236)
- François Bénard (ORCID: https://orcid.org/0000-0001-7995-3581)
- Sara Harsini (ORCID: https://orcid.org/0000-0001-6196-6982)
- Amirhosein Toosi (ORCID: https://orcid.org/0000-0001-6432-9428)
- Carlos Uribe (ORCID: https://orcid.org/0000-0003-3127-7478)
Institutions
- Microsoft (United States) (US)
- University of British Columbia (CA)
Publication Details
- Journal
- Cancers
- Published
- 2025-05-03
- DOI
- https://doi.org/10.3390/cancers17091563
- Primary Topic
- Advanced Neural Network Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Mitacs
- Health Canada
- Canadian Institutes of Health Research