Cell Nuclei segmentation in Pap smear images using Optimized Binarization technique with Adaptive Wiener Filter
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Date
2013
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Abstract
Cervical cancer is the second leading reason o f death among women in India. The most
common screening technique is Pap smear test which is used to detect abnormal growth
o f cervical cells at an early stage. The accuracy rate o f cervical cancer diagnosis using Pap
smear images depends on the segmentation o f the cell nuclei. This paper proposes the
optimized binarizatidh technique with Adaptive Wiener Filter (AWF) for the cell nuclei
segmentation fn ^ ^o key steps. First, the Adaptive Wiener Filter is used for the noise removal
as well as to preserve the details o f the Pap smear images. Followed by, the threshold value
is being obtained from the sure shrinkage method. Ant Colony Optimization and Particle
swarm optimization for the exact segmentation o f cell nuclei from Pap smear images. Due to
the limitations in the segmentation techniques, the loss o f cell nuclei gets a raise which
affects the quality and efficiency o f cervical cancer detection. To know about the loss in the
number o f cell nuclei during segmentation step, the number o f nuclei is counted from the
segmented images and cell count results are compared with each other. From the results, it is
found that the Adaptive Wiener Filter in combination with PSO based threshold segmentation
performs well in terms o f MSE, cell nuclei count, sensitivity and specificity.