Segmentation in Cervical Cancer Detection: A Key Step in Early Diagnosis
Keywords:
Cervical cancer, Contouring, Papillomavirus, Segmentation, Three Segnet ArchitectureAbstract
Cervical cancer refers to a type of cancer that develops in the cells of the cervix, which's the lower part of the uterus connecting to the vagina. Many cancers affect people all over the world. One of them is cervical cancer. Preventing the disease requires early detection and successful treatment rather than recognizing the issue at an advanced stage. These precautions can help prevent deadly cancer and contribute to a healthy life. This cancer can be treated well if it is detected early by a medical checkup for HPV lesions and risk factors for malignant cervix formation It is commonly triggered by the papillomavirus (HPV) a sexually transmitted infection. Globally cervical cancer ranks as the most prevalent cancer among women with around 570,000 new cases being diagnosed every year. Fortunately, this form of cancer is highly preventable through screenings and HPV vaccinations effectively reducing the risk of its development. Our research paper primarily focuses on enhancing cancer diagnosis and analysis by employing various techniques such as Contour segmentation, fitness score assessment, detection rate calculation, identification of optimal threshold values, geometric mean analysis, ROI examination, and three-segnet architecture. According to our research, we achieved a detection rate of 85%, a fitness score of 95%, a geometric mean of 90%, and positive results in the ROI examination. As a result of improving our techniques, we can provide better results for all images, resulting in better diagnosis and treatment. Continuing to innovate in medical imaging is crucial for providing the best possible care for cervical cancer patients.
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