Intervertebral disc anomaly intelligent classification system based on deep learning, IDAICS
This deep learning-based classification approach provides an efficient and reliable alternative to manual assessment, enabling automated diagnosis of intervertebral disc abnormalities. It offers significant potential to enhance clinical decision-making and improve spinal health management outcomes.
Authors
- Yu Chen (ORCID: https://orcid.org/0000-0002-2216-6234)
- Rong Fan (ORCID: https://orcid.org/0000-0002-5922-483X)
- Yuchen Qian (ORCID: https://orcid.org/0009-0004-6567-8792)
- Yusen Qiao (ORCID: https://orcid.org/0000-0001-7654-8636)
- Yuqing Yang (ORCID: https://orcid.org/0000-0002-3536-167X)
- Zhiheng Gao
- Lei Xing (ORCID: https://orcid.org/0009-0004-8910-6131)
- Yonggang Li (ORCID: https://orcid.org/0000-0002-6811-3429)
- Yu Wang (ORCID: https://orcid.org/0000-0001-7288-9150)
- Haifu Sun
Institutions
- Soochow University (CN)
- First Affiliated Hospital of Soochow University (CN)
Publication Details
- Journal
- Frontiers in Radiology
- Published
- 2025-09-09
- DOI
- https://doi.org/10.3389/fradi.2025.1646008
- Citations
- 1
- Primary Topic
- Medical Imaging and Analysis
- Type
- article
- Field-Weighted Citation Impact
- 0.67