Image Registration based Cervical Cancer Detection and Segmentation Using ANFIS Classifier

Document Type : Research Articles


1 ECE, Dhanalakshmi Srinivasan Engineering College, Tamilnadu, India.

2 EEE, GCE Salem, Tamilnadu, India.


Cervical cancer is the leading cancer in women around the world. In this paper, Adaptive Neuro Fuzzy Inference
System (ANFIS) classifier based cervical cancer detection and segmentation methodology is proposed. This proposed
system consists of the following stages as Image Registration, Feature extraction, Classifications and Segmentation.
Fast Fourier Transform (FFT) is used for image registration. Then, Grey Level Co-occurrence Matrix (GLCM), Grey
level and trinary features are extracted from the registered cervical image. Next, these extracted features are trained
and classified using ANFIS classifier. Morphological operations are now applied over the classified cervical image
to detect and segment the cancer region in cervical images. Simulations on large cervical image dataset demonstrate
that the proposed cervical cancer detection and segmentation methodology outperforms the state of-the-art methods in
terms of sensitivity, specificity and accuracy.




Main Subjects