Computer Aided Detection of Cervical Cancer Using Pap Smear Images Based on Adaptive Neuro Fuzzy Inference System Classifier

被引:40
作者
Sukumar, P. [1 ]
Gnanamurthy, R. K. [2 ]
机构
[1] Nandha Engn Coll, Dept Elect & Commun Engn, Erode 638052, Tamil Nadu, India
[2] SKP Engn Coll, Dept Elect & Commun Engn, Tiruvannamalai 606611, Tamil Nadu, India
关键词
Pap Smear; Cervical Cancer; Image Analysis; ANFIS Classifier; Medical Imaging; CELL-NUCLEI; SEGMENTATION; EXTRACTION;
D O I
10.1166/jmihi.2016.1690
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
Pap smear is a screening methodology for cervix cancer detection and diagnosis. The Pap smear images of cervical region are used to detect the abnormality of the cervical cells. In this Paper, the computer aided automatic detection and diagnosis method for cervix cancer using Pap smear image is proposed. The proposed methodology consists of the following stages as preprocessing, feature extraction, nuclei region segmentation and classification. Morphological operations are used to segment the nuclei cell region. The Grey level, wavelet and GLCM (Grey level co-occurrence matrix) features are extracted from normal and dysplastic cell nucleus. These extracted features are trained and classified using ANFIS (Adaptive neuro fuzzy inference system) classifier. The proposed method achieved 92.68% sensitivity, 99.65% specificity and 98.74% accuracy for dysplastic cell segmentation.
引用
收藏
页码:312 / 319
页数:8
相关论文
共 15 条
[1]  
[Anonymous], INT J MULTIMED UBIQU
[2]  
Aswathy S, 2012, INDIAN J MED RES, V136, P205
[3]  
Bamford P., 1996, APRS IMAGE SEGMENTAT, P75
[4]   Segmentation of cervical cell nuclei in high-resolution microscopic images: A new algorithm and a web-based software framework [J].
Bergmeir, Christoph ;
Garcia Silvente, Miguel ;
Manuel Benitez, Jose .
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE, 2012, 107 (03) :497-512
[5]  
Chen Y-F., 2013, IEEE J BIOMED HEALTH, V18, P156
[6]   Semi-Automatic Segmentation and Classification of Pap Smear Cells [J].
Chen, Yung-Fu ;
Huang, Po-Chi ;
Lin, Ker-Cheng ;
Lin, Hsuan-Hung ;
Wang, Li-En ;
Cheng, Chung-Chuan ;
Chen, Tsung-Po ;
Chan, Yung-Kuan ;
Chiang, John Y. .
IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS, 2014, 18 (01) :94-108
[7]   Automatic image segmentation by integrating color-edge extraction and seeded region growing [J].
Fan, JP ;
Yau, DKY ;
Elmagarmid, AK ;
Aref, WG .
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2001, 10 (10) :1454-1466
[8]   An Automated Method for Segmentation of Epithelial Cervical Cells in Images of ThinPrep [J].
Harandi, Negar M. ;
Sadri, Saeed ;
Moghaddam, Noushin A. ;
Amirfattahi, Rassul .
JOURNAL OF MEDICAL SYSTEMS, 2010, 34 (06) :1043-1058
[9]  
Kale Asli, 2010, Proceedings of the 2010 20th International Conference on Pattern Recognition (ICPR 2010), P2399, DOI 10.1109/ICPR.2010.587
[10]   Cooperation of color pixel classification schemes and color watershed: A study for microscopic images [J].
Lezoray, O ;
Cardot, H .
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2002, 11 (07) :783-789