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 proceedingConference contribution

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 languageEnglish
Title of host publication2021 IEEE International Conference on Consumer Electronics, ICCE 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728197661
DOIs
Publication statusPublished - 2021 Jan 10
Event2021 IEEE International Conference on Consumer Electronics, ICCE 2021 - Las Vegas, United States
Duration: 2021 Jan 102021 Jan 12

Publication series

NameDigest of Technical Papers - IEEE International Conference on Consumer Electronics
Volume2021-January
ISSN (Print)0747-668X

Conference

Conference2021 IEEE International Conference on Consumer Electronics, ICCE 2021
Country/TerritoryUnited States
CityLas Vegas
Period21/1/1021/1/12

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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