Cell Nuclear Segmentation of B-ALL Images Based on MSFF-SegNeXt
The results show that MSFF-SegNeXt outperforms existing models in managing the complexities of cell nucleus segmentation, particularly in capturing detailed edge structures. This advancement offers a robust and reliable solution for subsequent morphological analysis of B-ALL single cells.
Authors
- Yipei Wang
- Zhigang Hu (ORCID: https://orcid.org/0000-0003-1243-014X)
- Aoru Ge
- Kaiwen Cao (ORCID: https://orcid.org/0009-0000-9723-306X)
- Xinzheng Wang (ORCID: https://orcid.org/0000-0001-8757-8697)
- Cuisi Ou
Institutions
- Henan University of Science and Technology (CN)
Publication Details
- Journal
- Journal of Multidisciplinary Healthcare
- Published
- 2024-12-01
- DOI
- https://doi.org/10.2147/jmdh.s492655
- Citations
- 2
- Primary Topic
- Digital Imaging for Blood Diseases
- Type
- article
- Field-Weighted Citation Impact
- 0.50