Hybrid feature fusion in cervical cancer cytology: a novel dual-module approach framework for lesion detection and classification using radiomics, deep learning, and reproducibility
ObjectiveCervical cancer screening through cytology remains the gold standard for early detection, but manual analysis is time-consuming, labor-intensive, and prone to inter-observer variability. This study proposes an automated deep learning-based framework that integrates lesion detection, feature...
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| Main Authors: | Shurong Niu, Lili Zhang, Lina Wang, Xue Zhang, Erniao Liu |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2025-08-01
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| Series: | Frontiers in Oncology |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fonc.2025.1595980/full |
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