Deep learning diagnosis of hepatic echinococcosis based on dual-modality plain CT and ultrasound images: a large-scale, multicenter, diagnostic study
The multimodal deep learning diagnostic system that integrates CT and ultrasound significantly increases the diagnosis accuracy of HCE, liver cysts, and liver abscesses. It beats standard single-modal approaches and physician diagnoses by lowering misdiagnosis rates and increasing diagnostic reliability. It emphasizes the promise of multimodal imaging systems in tackling diagnostic issues in low-resource areas, opening the path for improved medical care accessibility and outcomes.
Authors
- Yajin Chen (ORCID: https://orcid.org/0000-0002-2419-6330)
- Jihao Zhang (ORCID: https://orcid.org/0000-0001-6192-4862)
- Hewei Tang (ORCID: https://orcid.org/0000-0001-5046-4637)
- Meng Yuan (ORCID: https://orcid.org/0000-0002-9248-3294)
- Jie Zhang (ORCID: https://orcid.org/0000-0002-2178-0558)
- Jie Chen (ORCID: https://orcid.org/0000-0003-0290-3206)
- Xiong Chen (ORCID: https://orcid.org/0000-0003-2878-7522)
Institutions
- Sun Yat-sen University (CN)
- Sun Yat-sen Memorial Hospital (CN)
- People's Hospital of Xinjiang Uygur Autonomous Region (CN)
Publication Details
- Journal
- International Journal of Surgery
- Published
- 2025-04-11
- DOI
- https://doi.org/10.1097/js9.0000000000002486
- Primary Topic
- Amoebic Infections and Treatments
- Type
- article
- Field-Weighted Citation Impact
- 0.00