CT-Guided 3D Super-Resolution Method for Left Atrial Model

Jae Ik Yoo; Hong Kyu Shin; Seung Park; Dae In Lee; Sung Jea Ko

doi:10.1109/ICCE50685.2021.9427717

CT-Guided 3D Super-Resolution Method for Left Atrial Model

Jae Ik Yoo, Hong Kyu Shin, Seung Park, Dae In Lee, Sung Jea Ko

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Citation (Scopus)

Abstract

In atrial fibrillation treatment, it is important to visualize and analyze an accurate left atrial (LA) model from cardiac computed tomography (CT) images. In recent years, 3D-CNNs have been applied to acquire an accurate LA model from CT images. However, due to the hardware limitations, only LA models with low-resolution can be obtained. In this paper, we present a 3D super-resolution method that utilizes the high-resolution original CT volume as a guide by combining features with the same receptive field in layer level. Experimental results show that the proposed method achieves high performance in terms of quantitative and qualitative evaluations.

Original language	English
Title of host publication	2021 IEEE International Conference on Consumer Electronics, ICCE 2021
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781728197661
DOIs	https://doi.org/10.1109/ICCE50685.2021.9427717
Publication status	Published - 2021 Jan 10
Event	2021 IEEE International Conference on Consumer Electronics, ICCE 2021 - Las Vegas, United States Duration: 2021 Jan 10 → 2021 Jan 12

Publication series

Name	Digest of Technical Papers - IEEE International Conference on Consumer Electronics
Volume	2021-January
ISSN (Print)	0747-668X

Conference

Conference	2021 IEEE International Conference on Consumer Electronics, ICCE 2021
Country/Territory	United States
City	Las Vegas
Period	21/1/10 → 21/1/12

Bibliographical note

Funding Information:
ACKNOWLEDGMENT This work was supported by the Institute for Information & communications Technology Promotion(IITP) grant funded by the Korea government(MSIT) (2017-0-00250, Intelligent Defense Boundary Surveillance Technology Using Collaborative Reinforced Learning of Embedded Edge Camera and Image Analysis).

Publisher Copyright:
© 2021 IEEE.

Keywords

3D-CNN
atrial fibrillation
computed tomography
deep learning
left atrial model
super-resolution

ASJC Scopus subject areas

Industrial and Manufacturing Engineering
Electrical and Electronic Engineering

Access to Document

10.1109/ICCE50685.2021.9427717

Cite this

Yoo, J. I., Shin, H. K., Park, S., Lee, D. I., & Ko, S. J. (2021). CT-Guided 3D Super-Resolution Method for Left Atrial Model. In 2021 IEEE International Conference on Consumer Electronics, ICCE 2021 Article 9427717 (Digest of Technical Papers - IEEE International Conference on Consumer Electronics; Vol. 2021-January). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICCE50685.2021.9427717

CT-Guided 3D Super-Resolution Method for Left Atrial Model. / Yoo, Jae Ik; Shin, Hong Kyu; Park, Seung et al.
2021 IEEE International Conference on Consumer Electronics, ICCE 2021. Institute of Electrical and Electronics Engineers Inc., 2021. 9427717 (Digest of Technical Papers - IEEE International Conference on Consumer Electronics; Vol. 2021-January).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Yoo, JI, Shin, HK, Park, S, Lee, DI & Ko, SJ 2021, CT-Guided 3D Super-Resolution Method for Left Atrial Model. in 2021 IEEE International Conference on Consumer Electronics, ICCE 2021., 9427717, Digest of Technical Papers - IEEE International Conference on Consumer Electronics, vol. 2021-January, Institute of Electrical and Electronics Engineers Inc., 2021 IEEE International Conference on Consumer Electronics, ICCE 2021, Las Vegas, United States, 21/1/10. https://doi.org/10.1109/ICCE50685.2021.9427717

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abstract = "In atrial fibrillation treatment, it is important to visualize and analyze an accurate left atrial (LA) model from cardiac computed tomography (CT) images. In recent years, 3D-CNNs have been applied to acquire an accurate LA model from CT images. However, due to the hardware limitations, only LA models with low-resolution can be obtained. In this paper, we present a 3D super-resolution method that utilizes the high-resolution original CT volume as a guide by combining features with the same receptive field in layer level. Experimental results show that the proposed method achieves high performance in terms of quantitative and qualitative evaluations.",

keywords = "3D-CNN, atrial fibrillation, computed tomography, deep learning, left atrial model, super-resolution",

author = "Yoo, {Jae Ik} and Shin, {Hong Kyu} and Seung Park and Lee, {Dae In} and Ko, {Sung Jea}",

note = "Funding Information: ACKNOWLEDGMENT This work was supported by the Institute for Information & communications Technology Promotion(IITP) grant funded by the Korea government(MSIT) (2017-0-00250, Intelligent Defense Boundary Surveillance Technology Using Collaborative Reinforced Learning of Embedded Edge Camera and Image Analysis). Publisher Copyright: {\textcopyright} 2021 IEEE.; 2021 IEEE International Conference on Consumer Electronics, ICCE 2021 ; Conference date: 10-01-2021 Through 12-01-2021",

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N1 - Funding Information: ACKNOWLEDGMENT This work was supported by the Institute for Information & communications Technology Promotion(IITP) grant funded by the Korea government(MSIT) (2017-0-00250, Intelligent Defense Boundary Surveillance Technology Using Collaborative Reinforced Learning of Embedded Edge Camera and Image Analysis). Publisher Copyright: © 2021 IEEE.

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N2 - In atrial fibrillation treatment, it is important to visualize and analyze an accurate left atrial (LA) model from cardiac computed tomography (CT) images. In recent years, 3D-CNNs have been applied to acquire an accurate LA model from CT images. However, due to the hardware limitations, only LA models with low-resolution can be obtained. In this paper, we present a 3D super-resolution method that utilizes the high-resolution original CT volume as a guide by combining features with the same receptive field in layer level. Experimental results show that the proposed method achieves high performance in terms of quantitative and qualitative evaluations.

AB - In atrial fibrillation treatment, it is important to visualize and analyze an accurate left atrial (LA) model from cardiac computed tomography (CT) images. In recent years, 3D-CNNs have been applied to acquire an accurate LA model from CT images. However, due to the hardware limitations, only LA models with low-resolution can be obtained. In this paper, we present a 3D super-resolution method that utilizes the high-resolution original CT volume as a guide by combining features with the same receptive field in layer level. Experimental results show that the proposed method achieves high performance in terms of quantitative and qualitative evaluations.

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CT-Guided 3D Super-Resolution Method for Left Atrial Model

Abstract

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Bibliographical note

Keywords

ASJC Scopus subject areas

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