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Nucleus segmentation of cervical cytology images based on multi-scale fuzzy clustering algorithm
- Source :
- Bioengineered, Bioengineered, Vol 11, Iss 1, Pp 484-501 (2020)
- Publication Year :
- 2020
- Publisher :
- Taylor & Francis, 2020.
-
Abstract
- In the screening of cervical cancer cells, accurate identification and segmentation of nucleus in cell images is a key part in the early diagnosis of cervical cancer. Overlapping, uneven staining, poor contrast, and other reasons present challenges to cervical nucleus segmentation. We propose a segmentation method for cervical nuclei based on a multi-scale fuzzy clustering algorithm, which segments cervical cell clump images at different scales. We adopt a novel interesting degree based on area prior to measure the interesting degree of the node. The application of these two methods not only solves the problem of selecting the categories number of the clustering algorithm but also greatly improves the nucleus recognition performance. The method is evaluated by the IBSI2014 and IBSI2015 public datasets. Experiments show that the proposed algorithm has greater advantages than the state-of-the-art cervical nucleus segmentation algorithms and accomplishes high accuracy nucleus segmentation results.<br />Graphical Abstract
- Subjects :
- Fuzzy clustering
Computer science
Uterine Cervical Neoplasms
Bioengineering
02 engineering and technology
Applied Microbiology and Biotechnology
030218 nuclear medicine & medical imaging
multi-scale fuzzy clustering algorithm
03 medical and health sciences
0302 clinical medicine
0202 electrical engineering, electronic engineering, information engineering
medicine
Cluster Analysis
Humans
Segmentation
Cervical cancer screening
Cluster analysis
cervical cell
Cervical cancer
Cell Nucleus
Node (networking)
General Medicine
Special issue on Advances in Artificial Intelligence in Biomedical Imaging
medicine.disease
Identification (information)
medicine.anatomical_structure
nucleus segmentation
Key (cryptography)
020201 artificial intelligence & image processing
Female
Algorithm
Nucleus
TP248.13-248.65
Algorithms
Biotechnology
Subjects
Details
- Language :
- English
- ISSN :
- 21655987 and 21655979
- Volume :
- 11
- Issue :
- 1
- Database :
- OpenAIRE
- Journal :
- Bioengineered
- Accession number :
- edsair.doi.dedup.....608497b8d5a0e0b1f2fdb266e6ea33c3