A Review: Pap Smear Analysis Based on Image Processing Approach

Abstract

Nowadays, in the hospital, cervical cancer is in the higher rank (number 2) of the most popular cancer among ladies in the world. This cancer develops in the woman’s cervix which the womb is the entrance. Mostly, doctors in the hospital having trouble to identify the cancer cell because the nucleus of the cell is sometimes slightly hard to observe with eyes. The nucleus of the normal cell is in a smaller size compared to the abnormal nucleus. The abnormal nucleus has a bigger size, which sometimes, the size cannot be identified accurately by seeing with bare eyes to classify the stages of cervical cancer. This is because every doctor has different perspectives to observe the classification of the stages of cancer by observing the nucleus without accurate dimensionality reduction in the accuracy of the classifier. Recently, many researchers proposed a method to detect and classify the Pap smear cell images for cervical cancer diagnosis. This approach may improve the accuracy of the detection and the classification which to show better performance with the balance data and samples precisely. Some of the patients got the result that they are on stage 2, however after re-testing, they actually on stage 4 which the chance to heal is very low. This happens because the doctor can’t find the accurate balance data and sample precisely. In this paper, a comprehensive review of cervical detection based on segmentation nucleus and classification was studied.

Meticulous Review: Cutting-Edge Cervix Cancer Stratification Using Image Processing And Machine Learning

“…Based on the Statistics derived from the WHO Global Health Estimates-2019 [4], [5], [6], out of 656 300 000 total population of females in India, 4 191 000 females died due to cervical cancer [7]. Even though cervical cancer falls into a category of cancers that can be readily prevented through vaccination [2] and has an extended pre-malignant phase [8], [9], [10] which can be utilized for detection and treatment of the disease, lack of awareness is the key reason for this mortality rate in developing countries [11], [9], [12], [13], [14]. Cervical cancer is developed in the cervix area of the vagina the entrance of the uterus in women [3].…”

Model of Watershed Segmentation in Deep Learning Method to Improve Identification of Cervical Cancer at Overlay Cells

“…There are still weaknesses in existing techniques, resulting in low accuracy for some cell classes [8]. The use of segmentation techniques for overlapping cells is still low [9]. Therefore, research in developing segmentation techniques to identify overlapping cells in CC images is needed.…”

Medical Image Registration at Pap Smear for Early Identification of Cervical Cancer

“…This information is fundamental in detecting cancerous or precancerous lesions [13]. The results of segmentation can affect all processes of medical image analysis in classifying lesions [14], but the overlap of cells is still low [15] and even poor [16].…”