Gastrointestinal Mucosal Problems Classification with Deep Learning
Mohammadhasan Goharian Vahid Goharian Hamidreza Bolhasani
Gastrointestinal mucosal changes can cause cancers after some years and early
diagnosing them can be very useful to prevent cancers and early treatment. In
this article, 8 classes of mucosal changes and anatomical landmarks including
Polyps, Ulcerative Colitis, Esophagitis, Normal Z-Line, Normal Pylorus, Normal
Cecum, Dyed Lifted Polyps, and Dyed Lifted Margin were predicted by deep
learning. We used neural networks in this article. It is a black box artificial
intelligence algorithm that works like a human neural system. In this article,
Transfer Learning (TL) based on the Convolutional Neural Networks (CNNs), which
is one of the well-known types of neural networks in image processing is used.
We compared some famous CNN architecture including VGG, Inception, Xception,
and ResNet. Our best model got 93% accuracy in test images. At last, we used
our model in some real endoscopy and colonoscopy movies to classify problems.