A mobile-based image analysis system for cervical cancer detection
Saka Abiola Monsur, Steve Adetunji Adeshina, Shivani Sud, Winston Oluwole Soboyejo · 2017
Cervical cancer is the third major killer disease in developed and developing countries. Whereas screening and other preventive measures reduce the mortality in developed countries, mortality rate still remains very high in developing countries. This project focuses on the analysis of digital image of the cervix, captured with a low-level camera and under a contrast agent (the visual inspection with acetic acid (VIA)). Gaussian and mean filter techniques were used to remove the speckles. A segmentation algorithm was used to isolate the Region of Interest (ROI) from the image. Additionally a Canny edge detection algorithm was used to find edges. Furthermore, quantification and classification of the images were done. An android application was used to integrated all the above. This allows usage in rural settings. The results obtained were quite satisfactory (Specificity 79% and Sensitivity of 83%).