TY - GEN
T1 - Endoscopic Image Clustering with Temporal Ordering Information Based on Dynamic Programming
AU - Harada, Shota
AU - Hayashi, Hideaki
AU - Bise, Ryoma
AU - Tanaka, Kiyohito
AU - Meng, Qier
AU - Uchida, Seiichi
N1 - Funding Information:
This work was partially supported by AMED Grant Number JP18lk1010028.
Publisher Copyright:
© 2019 IEEE.
PY - 2019/7
Y1 - 2019/7
N2 - In this paper, we propose a clustering method with temporal ordering information for endoscopic image sequences. It is difficult to collect a sufficient amount of endoscopic image datasets to train machine learning techniques by manual labeling. The clustering of endoscopic images leads to group-based labeling, which is useful for reducing the cost of dataset construction. Therefore, in this paper, we propose a clustering method where the property of endoscopic image sequences is fully utilized. For the proposed method, a deep neural network was used to extract features from endoscopic images, and clustering with temporal ordering information was solved by dynamic programming. In the experiments, we clustered the esophagogastroduodenoscopy images. From the results, we confirmed that the performance was improved by using the sequential property.
AB - In this paper, we propose a clustering method with temporal ordering information for endoscopic image sequences. It is difficult to collect a sufficient amount of endoscopic image datasets to train machine learning techniques by manual labeling. The clustering of endoscopic images leads to group-based labeling, which is useful for reducing the cost of dataset construction. Therefore, in this paper, we propose a clustering method where the property of endoscopic image sequences is fully utilized. For the proposed method, a deep neural network was used to extract features from endoscopic images, and clustering with temporal ordering information was solved by dynamic programming. In the experiments, we clustered the esophagogastroduodenoscopy images. From the results, we confirmed that the performance was improved by using the sequential property.
UR - http://www.scopus.com/inward/record.url?scp=85077896393&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85077896393&partnerID=8YFLogxK
U2 - 10.1109/EMBC.2019.8857011
DO - 10.1109/EMBC.2019.8857011
M3 - Conference contribution
C2 - 31946675
AN - SCOPUS:85077896393
T3 - Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
SP - 3681
EP - 3684
BT - 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019
Y2 - 23 July 2019 through 27 July 2019
ER -