Detection of Stages of Cervical Cancer using Deep Learning
Priyadarshini Chatterjee · 2023
Deep Learning approaches have gained importance recently specially in the field of medical image processing. They are widely used for image segmentation, analysis of an image and also used as image preprocessing tool. Amongst the other cancer, cervical cancer is one of the deadliest. Moreover, if they are not detected earlier can be fatal. Although, there are many algorithms that help to detect cancer, but their accuracy varies. The accuracy of the stages of cancer detection depends mostly on segmentation. More the accurate is the segmentation, the accuracy of the stages of cancer detection will increase. This article proposed an algorithm to segment a crowded nucleus using a neural network after preprocessing of the image. Then the cytoplasm of the nucleus is sent for feature extraction which predicts the stages of cancer. The proposed method compares the algorithm on terms of false positive, false negative, true positive and true negative. The results are tabulated in the result section of the paper.