A MapReduce-like Deep Learning Model for the Depth Estimation of Periodontal Pockets

Yusuke Moriyama, Chonho Lee, Susumu Date, Yoichiro Kashiwagi, Yuki Narukawa, Kazunori Nozaki, Shinya Murakami

2019

Abstract

This paper explores the feasibility of diagnostic imaging using a deep learning-based model, applicable to periodontal disease, especially periodontal pocket screening. Having investigated conventional approaches, we find two difficulties to estimate the pocket depth of teeth from oral images. One is the feature extraction of Region of Interest (ROI), which is pocket region, caused by the small ROI, and another is tooth identification caused by the high heterogeneity of teeth (e.g., in size, shape, and color). We propose a MapReduce-like periodontal pocket depth estimation model that overcomes the difficulties. Specifically, a set of MapTasks is executed in parallel, each of which only focuses on one of the multiple views (e.g., front, left, right, etc.) of oral images and runs an object detection model to extract the high-resolution pocket region images. After a classifier estimates pocket depth from the extracted images, ReduceTasks aggregate the pocket depth with respect to each pocket. Experimental results show that the proposed model effectively works to achieve the estimation accuracy to 76.5 percent. Besides, we verify the practical feasibility of the proposed model with 91.7 percent accuracy under the condition that a screening test judges severe periodontitis (6 mm or more).

Paper Citation

in Harvard Style

Moriyama Y., Lee C., Date S., Kashiwagi Y., Narukawa Y., Nozaki K. and Murakami S. (2019). A MapReduce-like Deep Learning Model for the Depth Estimation of Periodontal Pockets. In Proceedings of the 12th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2019) - Volume 5: HEALTHINF; ISBN 978-989-758-353-7, SciTePress, pages 388-395. DOI: 10.5220/0007405703880395

in Bibtex Style

@conference{healthinf19,
author={Yusuke Moriyama and Chonho Lee and Susumu Date and Yoichiro Kashiwagi and Yuki Narukawa and Kazunori Nozaki and Shinya Murakami},
title={A MapReduce-like Deep Learning Model for the Depth Estimation of Periodontal Pockets},
booktitle={Proceedings of the 12th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2019) - Volume 5: HEALTHINF},
year={2019},
pages={388-395},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007405703880395},
isbn={978-989-758-353-7},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 12th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2019) - Volume 5: HEALTHINF
TI - A MapReduce-like Deep Learning Model for the Depth Estimation of Periodontal Pockets
SN - 978-989-758-353-7
AU - Moriyama Y.
AU - Lee C.
AU - Date S.
AU - Kashiwagi Y.
AU - Narukawa Y.
AU - Nozaki K.
AU - Murakami S.
PY - 2019
SP - 388
EP - 395
DO - 10.5220/0007405703880395
PB - SciTePress