Esophageal Cancer Detection Using Feed-Forward Neural Network

Esophageal malignant growth is probably the deadliest kind of disease in people. It positions seventh as far as disease and 6th as far as passings worldwide, as indicated by the insights of the World Health Organization for the year 2020. That is why we aim to develop a computer system that works on the early detection of esophageal cancer using modern image processing techniques and algorithms. To reduce the death rate by helping
specialized doctors to detect it in its early condition. In our research, we relied on the use the Fuzzy C-Means (FCM) algorithm at the stage of clustering and segmentation. In addition, it could use the Convolutional Neural Network (CNN) algorithm in the detection stage. After applying the proposed system to 100 color esophagogastroduodenoscopy images that we downloaded from the Kaggle website, we obtained an accuracy of up to 95%. Note that we did not find researchers who used this data set in their systems to the best of our knowledge. It has been noticed that using the FCM algorithm with the CNN algorithm added a good character in detecting esophageal cancer, although the FCM algorithm needs a lot of development to get the results.

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