Abstract
This work presents a unique automated technique for the identification of cervical cancer cells using image processing and MATLAB. The method accurately detects abnormal cervical cells by employing complex algorithms for segmentation, feature extraction, and image enhancement. The proposed method performs well in differentiating between normal and abnormal cells. This study might improve patient outcomes and early detection rates by making cervical cancer screening more effective. Cervical cancer ranks as the second most prevalent cancer in women of all ages. Because it has no symptoms, this cancer cannot be detected in its early stages. The main problem with this cancer is that it doesn't show any signs until it has progressed to an advanced stage. This is related to both the cancer and the scarcity of pathologists who can do cancer screenings. Cervical cancer screening is recommended for a number of reasons, including dread of the repercussions of cervical cancer, a sense of risk, the need for complete examination, diagnosis, and treatment of all illnesses to preserve good health, and the need to keep communication lines open with medical professionals. Ignorance is one of the biggest barriers to repeat screening. Two significant barriers are a lack of reminders and a poor comprehension of the importance of ongoing screening.
Citations
IRE Journals:
Venkata Chandu K. , Balanaga Sairam K. , Yaswanth K. , Surya Prakash J. , Devi S.
"Cervical Cancer Cell Detection Using Image Processing and Matlab" Iconic Research And Engineering Journals Volume 7 Issue 7 2024 Page 88-92
IEEE:
Venkata Chandu K. , Balanaga Sairam K. , Yaswanth K. , Surya Prakash J. , Devi S.
"Cervical Cancer Cell Detection Using Image Processing and Matlab" Iconic Research And Engineering Journals, 7(7)
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