Mammogram Analysis with YOLO Models on an Affordable Embedded System
The current research landscape has not yet integrated advanced YOLO versions for embedded deployment in mammography. This method could facilitate screening in clinics without high-end workstations, demonstrating the feasibility of deploying CAD systems in low-resource environments and underscoring its potential for real-world clinical applications.
Authors
- Methininat Lertkowit
- Anongnat Intasam
- Yuttachon Promworn
- Somchai Thanasitthichai
- Aniwat Juhong (ORCID: https://orcid.org/0000-0002-9115-9767)
- Sirihattaya Khwayotha
- Wibool Piyawattanametha (ORCID: https://orcid.org/0000-0002-2228-8485)
- Titipon Jiranantanakorn
- Soonthorn Thawornwanchai
- Nicholas Piyawattanametha
- Pakpawee Pichayakul
- Sarawan Sriwanichwiphat
- Nucharee Phakwapee
Institutions
- National Cancer Institute of Thailand (TH)
- Udon Thani Hospital (TH)
- Michigan State University (US)
- King Mongkut's Institute of Technology Ladkrabang (TH)
Publication Details
- Journal
- Cancers
- Published
- 2025-12-25
- DOI
- https://doi.org/10.3390/cancers18010070
- Primary Topic
- AI in cancer detection
- Type
- article
- Field-Weighted Citation Impact
- 0.00