Paper Info
Title
Nucleus classification and recognition of uterine cervical pap-smears using fuzzy ART algorithm
Abstract
Segmentation for the region of nucleus in the image of uterine cervical cytodiagnosis is known as the most difficult and important part in the automatic cervical cancer recognition system. In this paper, the region of nucleus is extracted from an image of uterine cervical cytodiagnosis using the HSI model. The characteristics of the nucleus are extracted from the analysis of morphemetric features, densitometric features, colorimetric features, and textural features based on the detected region of nucleus area. The classification criterion of a nucleus is defined according to the standard categories of the Bethesda system. The fuzzy ART algorithm is used to the extracted nucleus and the results show that the proposed method is efficient in nucleus recognition and uterine cervical Pap-Smears extraction.
Year
DOI
Venue
2006
10.1007/11903697_71
SEAL
Keywords
Field
DocType
colorimetric feature,densitometric feature,automatic cervical cancer recognition,nucleus recognition,hsi model,uterine cervical cytodiagnosis,classification criterion,bethesda system,uterine cervical pap-smears extraction,nucleus area,fuzzy art algorithm,nucleus classification,uterine cervical pap-smears
Cervical cancer,Bethesda system,Nucleus,Recognition system,Segmentation,Computer science,Fuzzy logic,Algorithm,Pap smears,Cervix uterus
Conference
Volume
ISSN
ISBN
4247
0302-9743
3-540-47331-9
Citations 
PageRank 
References 
1
0.93
2
Authors
3
Name
Order
Citations
PageRank
kwangbaek kim111043.94
Sungshin Kim221064.17
Kwee-Bo Sim324944.07