Kudo’s Classification for Colon Polyps Assessment Using a Deep Learning Approach

Sebastian Patino-Barrientos,Daniel Sierra-Sosa,Adel Elmaghraby,Cristian Castillo-Olea,Begonya Garcia-Zapirain

doi:10.3390/app10020501

Sebastian Patino-Barrientos, Daniel Sierra-Sosa + Show 3 more

Open Access

https://doi.org/10.3390/app10020501

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Abstract

Colorectal cancer (CRC) is the second leading cause of cancer death in the world. This disease could begin as a non-cancerous polyp in the colon, when not treated in a timely manner, these polyps could induce cancer, and in turn, death. We propose a deep learning model for classifying colon polyps based on the Kudo’s classification schema, using basic colonoscopy equipment. We train a deep convolutional model with a private dataset from the University of Deusto with and without using a VGG model as a feature extractor, and compared the results. We obtained 83% of accuracy and 83% of F1-score after fine tuning our model with the VGG filter. These results show that deep learning algorithms are useful to develop computer-aided tools for early CRC detection, and suggest combining it with a polyp segmentation model for its use by specialists.

Highlights

Colorectal cancer (CRC) is one of the most lethal cancer types in the world, is the second leading cause of cancer death in the world and ranks third in incidence with over 881,000 deaths and 1.8 million cases that were estimated to occur in 2018 [1]
To provide a computer-aided diagnosis tool for CRC prevention, we propose a deep learning algorithm based on any standard colonoscopy equipment that classifies polyps into high risk and low risk of malignancy based on pit patterns described by Kudo
Given that medical datasets are usually too small for training very deep neural networks effectively, this experiment supports the previously tested hypothesis that CNN features from nonmedical domains can be very effective when used with medical datasets [14]

Summary

Introduction

Colorectal cancer (CRC) is one of the most lethal cancer types in the world, is the second leading cause of cancer death in the world and ranks third in incidence with over 881,000 deaths and 1.8 million cases that were estimated to occur in 2018 [1]. This disease begins as a non-cancerous growth of glandular tissue on the colon’s or rectum’s inner lining known as a adenomatous polyp. In order to reduce false negatives, the medical personnel must remove all detected polyps during colonoscopy as there is no a perfect method to decide if a polyp is benign or malignant

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