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 | |
| 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
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