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@article{ART002698402},
author={Jung Whan Park and Kim, yoon and Kim, WooJin and Nam Seung Joo},
title={Automatic Anatomical Classification Model of Esophagogastroduodenoscopy Images Using Deep Convolutional Neural Networks for Guiding Endoscopic Photodocumentation},
journal={Journal of The Korea Society of Computer and Information},
issn={1598-849X},
year={2021},
volume={26},
number={3},
pages={19-28},
doi={10.9708/jksci.2021.26.03.019}

TY - JOUR
AU - Jung Whan Park
AU - Kim, yoon
AU - Kim, WooJin
AU - Nam Seung Joo
TI - Automatic Anatomical Classification Model of Esophagogastroduodenoscopy Images Using Deep Convolutional Neural Networks for Guiding Endoscopic Photodocumentation
JO - Journal of The Korea Society of Computer and Information
PY - 2021
VL - 26
IS - 3
PB - The Korean Society Of Computer And Information
SP - 19
EP - 28
SN - 1598-849X
AB - Esophagogastroduodenoscopy is a method commonly used for early diagnosis of upper gastrointestinal lesions. However, 10-20 percent of the gastric lesions are reported to be missed, due to human error. And countries including the US, the UK, and Japan, the World Endoscopy Organization (WEO) suggested guidelines about essential gastrointestinal parts to take pictures of so that all gastric lesions are observed. In this paper, we propose deep learning techniques for classification of anatomical sites, aiming for the system that informs practitioners whether they successfully did the gastroscopy without blind spots. The proposed model uses pre-processing modules and data augmentation techniques suitable for gastroscopy images. Not only does the experiment result with a maximum F1 score of 99.6%, but it also shows a error rate of less than 4% based on the actual data. Given the performance results, we found the model to be explainable with the potential to be utilized in the clinical area.
KW - Deep Learning;Medical Image Analysis;EsophagoGastroDuodenoscopy;Stomach Anatomy Site Classification;Image Processing
DO - 10.9708/jksci.2021.26.03.019
ER -

Jung Whan Park, Kim, yoon, Kim, WooJin and Nam Seung Joo. (2021). Automatic Anatomical Classification Model of Esophagogastroduodenoscopy Images Using Deep Convolutional Neural Networks for Guiding Endoscopic Photodocumentation. Journal of The Korea Society of Computer and Information, 26(3), 19-28.

Jung Whan Park, Kim, yoon, Kim, WooJin and Nam Seung Joo. 2021, "Automatic Anatomical Classification Model of Esophagogastroduodenoscopy Images Using Deep Convolutional Neural Networks for Guiding Endoscopic Photodocumentation", Journal of The Korea Society of Computer and Information, vol.26, no.3 pp.19-28. Available from: doi:10.9708/jksci.2021.26.03.019

Jung Whan Park, Kim, yoon, Kim, WooJin, Nam Seung Joo "Automatic Anatomical Classification Model of Esophagogastroduodenoscopy Images Using Deep Convolutional Neural Networks for Guiding Endoscopic Photodocumentation" Journal of The Korea Society of Computer and Information 26.3 pp.19-28 (2021) : 19.

Jung Whan Park, Kim, yoon, Kim, WooJin, Nam Seung Joo. Automatic Anatomical Classification Model of Esophagogastroduodenoscopy Images Using Deep Convolutional Neural Networks for Guiding Endoscopic Photodocumentation. 2021; 26(3), 19-28. Available from: doi:10.9708/jksci.2021.26.03.019

Jung Whan Park, Kim, yoon, Kim, WooJin and Nam Seung Joo. "Automatic Anatomical Classification Model of Esophagogastroduodenoscopy Images Using Deep Convolutional Neural Networks for Guiding Endoscopic Photodocumentation" Journal of The Korea Society of Computer and Information 26, no.3 (2021) : 19-28.doi: 10.9708/jksci.2021.26.03.019

Jung Whan Park; Kim, yoon; Kim, WooJin; Nam Seung Joo. Automatic Anatomical Classification Model of Esophagogastroduodenoscopy Images Using Deep Convolutional Neural Networks for Guiding Endoscopic Photodocumentation. Journal of The Korea Society of Computer and Information, 26(3), 19-28. doi: 10.9708/jksci.2021.26.03.019

Jung Whan Park; Kim, yoon; Kim, WooJin; Nam Seung Joo. Automatic Anatomical Classification Model of Esophagogastroduodenoscopy Images Using Deep Convolutional Neural Networks for Guiding Endoscopic Photodocumentation. Journal of The Korea Society of Computer and Information. 2021; 26(3) 19-28. doi: 10.9708/jksci.2021.26.03.019

Jung Whan Park, Kim, yoon, Kim, WooJin, Nam Seung Joo. Automatic Anatomical Classification Model of Esophagogastroduodenoscopy Images Using Deep Convolutional Neural Networks for Guiding Endoscopic Photodocumentation. 2021; 26(3), 19-28. Available from: doi:10.9708/jksci.2021.26.03.019

Jung Whan Park, Kim, yoon, Kim, WooJin and Nam Seung Joo. "Automatic Anatomical Classification Model of Esophagogastroduodenoscopy Images Using Deep Convolutional Neural Networks for Guiding Endoscopic Photodocumentation" Journal of The Korea Society of Computer and Information 26, no.3 (2021) : 19-28.doi: 10.9708/jksci.2021.26.03.019