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Application of Convolutional Neural Networks for Cervical Cancer Detection in Women’s Uterus | IEEE Conference Publication | IEEE Xplore

Application of Convolutional Neural Networks for Cervical Cancer Detection in Women’s Uterus


Abstract:

HPV infection is frequently the cause of cervical cancer, the fourth most prevalent type of cancer that mostly affects women’s cervixes. Early vaccination of women may be...Show More

Abstract:

HPV infection is frequently the cause of cervical cancer, the fourth most prevalent type of cancer that mostly affects women’s cervixes. Early vaccination of women may be the key to its eradication, but this effort is fraught with difficulties, particularly in middle-class or lower-income nations where access to healthcare is scarce. In this paper, a novel method for detecting cervical cancer using medical image processing techniques and Convolutional Neural Networks (CNNs) is presented. A serious health risk is cervical cancer, especially in areas with poor access to medical facilities. By using CNNs to analyze medical pictures, such as pap smears and cervical scans, the suggested approach seeks to overcome this difficulty by enabling the early identification of abnormalities in the cervical region that may be signs of cancer or precancerous lesions. Data collection, preprocessing, segmentation, feature extraction, model training, and evaluation are all steps in the workflow. The CNN model shows promising performance in reliably diagnosing cervical cancer by automatic feature extraction from labelled datasets. The efficacy of the suggested strategy is confirmed by evaluation measures including area under the ROC curve, sensitivity, specificity, and accuracy.
Date of Conference: 22-23 August 2024
Date Added to IEEE Xplore: 29 October 2024
ISBN Information:
Conference Location: Bangalore, India

References

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