loading page

Automated & Easy Diagnosis of Cervical Cancer From Onsite Easy Colposcopy Images
  • Devi Bhattarai,
  • Bishesh Khanal
Devi Bhattarai

Corresponding Author:[email protected]

Author Profile
Bishesh Khanal
Author Profile


Lifestyle and early diagnosis can bring a drastic change in  Cervical cancer patient Infections when diagnosed early enough that makes it easy to prevent. By the time symptoms appear, cancer might have manifested itself and begun to spread. Due to poor access to preventive and treatment services, a vast number of unfortunate deaths occur needlessly. Enhancing the prevalent method of treatment and diagnosis, deep learning models have been proved to be more precise and accurate than mere Visual Inspection by specialists. AI-assisted colposcopy reduces time and effort it takes for a gynecologist to gain an expertise and thus spares more time to improve other skills, training and activities.Here, we use Supervised(unsupervised) algorithms in order to classify the colposcopy images. To attain our target, we collect a large number of image datasets requested to ABC hospital and are categorized by our system to different stages of cancer, results of which can be further analyzed by specialists to imply appropriate clinical procedures of cure. The successful deployment promotes low-cost mobile technology to facilitate millions of women across the country who earlier had limited access to life-saving cancer tests. As the morbidity and mortality rates of cervix cancer are pretty high, early detection and treatment of the abnormal tissues or pre-cancerous cells is the ultimate solution to it. This study is useful to diagnose an early metamorphosis of cancerous cells more accurately and hence helps to drop down the death rate even in any low-middle resources areas of the country.
Keywords: Cervical Cancer, Deep learning, Colposcopy, Pap smear and HPV