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 |
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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 | |
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 |
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Volume | 2021-January |
ISSN (Print) | 0747-668X |
Conference
Conference | 2021 IEEE International Conference on Consumer Electronics, ICCE 2021 |
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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