Malignancy prediction for calcified thyroid nodules using deep learning based on ultrasound dynamic videos
A calcification-optimized DL model trained on dynamic ultrasound videos was proposed to efficiently and accurately predict the benign/malignant nature of calcified nodules. This tool shows promises as a non-invasive, interpretable tool for early PTC detection, supporting timely diagnosis and treatment planning.
Authors
- J. Huang (ORCID: https://orcid.org/0000-0001-8680-8323)
- Vicky Yang Wang
- Tingting Qian (ORCID: https://orcid.org/0000-0001-9015-9637)
- Ni Chen (ORCID: https://orcid.org/0000-0002-0663-3867)
- Hongyu Shen (ORCID: https://orcid.org/0000-0002-2146-9997)
- Sohaib Asif
- Dong Xu (ORCID: https://orcid.org/0000-0002-5202-4309)
- Yin Zheng
- Renyi Zhu
- Yahan Zhou
- Yang Zhang (ORCID: https://orcid.org/0000-0002-3588-4702)
Institutions
- Zhejiang Chinese Medical University (CN)
- Wenzhou Medical University (CN)
- Zhejiang Cancer Hospital (CN)
- Zhejiang Academy of Social Sciences (CN)
- Zhejiang Lab (CN)
- Hangzhou Hospital of Traditional Chinese Medicine (CN)
- First Hospital of Jiaxing (CN)
- Zhejiang Taizhou Hospital (CN)
- Hangzhou Medical College (CN)
- Hangzhou Cancer Hospital (CN)
Publication Details
- Journal
- Cancer Imaging
- Published
- 2025-11-10
- DOI
- https://doi.org/10.1186/s40644-025-00944-3
- Primary Topic
- Thyroid Cancer Diagnosis and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China