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arXiv · 2307.16198

Gastrointestinal Mucosal Problems Classification with Deep Learning

Mohammadhasan Goharian·Vahid Goharian·Hamidreza Bolhasani
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Abstract

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.

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Mohammadhasan Goharian, Vahid Goharian, Hamidreza Bolhasani. 2023-07-30. Gastrointestinal Mucosal Problems Classification with Deep Learning. https://arxiv.org/abs/2307.16198

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