Deep learning based motion correction in ultrasound microvessel imaging approach improves thyroid nodule classification
Abstract To address inter-frame motion artifacts in ultrasound quantitative high-definition microvasculature imaging (qHDMI), we introduced a novel deep learning-based motion correction technique. This approach enables the derivation of more accurate quantitative biomarkers from motion-corrected HDM...
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| Main Authors: | Manali Saini, Nicholas B. Larson, Mostafa Fatemi, Azra Alizad |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-05-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-025-02728-y |
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