SPP-SegNet and SE-DenseNet201: A Dual-Model Approach for Cervical Cell Segmentation and Classification
These results show that SPP-SegNet and SE-DenseNet201 can potentially automate cervical cell segmentation and classification, facilitating the early detection and diagnosis of cervical cancer.
Authors
- Betelhem Zewdu Wubineh (ORCID: https://orcid.org/0000-0002-4790-7449)
- Krzysztof Halawa (ORCID: https://orcid.org/0000-0001-6508-0468)
- Andrzej Rusiecki (ORCID: https://orcid.org/0000-0003-2239-1076)
Institutions
- Wrocław University of Science and Technology (PL)
- AGH University of Krakow (PL)
Publication Details
- Journal
- Cancers
- Published
- 2025-06-27
- DOI
- https://doi.org/10.3390/cancers17132177
- Citations
- 5
- Primary Topic
- AI in cancer detection
- Type
- article
- Field-Weighted Citation Impact
- 12.40