CT-TEE Image Registration for Surgical Navigation of Congenital Heart Disease Based on a Cycle Adversarial Network
文献类型：期刊论文
| 作者 | Lu, Yunfei1; Li, Bing2; Liu, Ningtao1; Chen, Jia-Wei1; Xiao, Li3; Gou, Shuiping1; Chen, Linlin1; Huang, Meiping4; Zhuang, Jian5 |
| 刊名 | COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE
 |
| 出版日期 | 2020-07-02 |
| 卷号 | 2020页码:8 |
| ISSN号 | 1748-670X |
| DOI | 10.1155/2020/4942121 |
| 英文摘要 | Transesophageal echocardiography (TEE) has become an essential tool in interventional cardiologist's daily toolbox which allows a continuous visualization of the movement of the visceral organ without trauma and the observation of the heartbeat in real time, due to the sensor's location at the esophagus directly behind the heart and it becomes useful for navigation during the surgery. However, TEE images provide very limited data on clear anatomically cardiac structures. Instead, computed tomography (CT) images can provide anatomical information of cardiac structures, which can be used as guidance to interpret TEE images. In this paper, we will focus on how to transfer the anatomical information from CT images to TEE images via registration, which is quite challenging but significant to physicians and clinicians due to the extreme morphological deformation and different appearance between CT and TEE images of the same person. In this paper, we proposed a learning-based method to register cardiac CT images to TEE images. In the proposed method, to reduce the deformation between two images, we introduce the Cycle Generative Adversarial Network (CycleGAN) into our method simulating TEE-like images from CT images to reduce their appearance gap. Then, we perform nongrid registration to align TEE-like images with TEE images. The experimental results on both children' and adults' CT and TEE images show that our proposed method outperforms other compared methods. It is quite noted that reducing the appearance gap between CT and TEE images can benefit physicians and clinicians to get the anatomical information of ROIs in TEE images during the cardiac surgical operation. |
| 资助项目 | Natural Science Foundation of Shaanxi Province[2019ZDLGY03-02-02] ; Research Plan of Improving Public Scientific Quality in Shaanxi Province[E219360001] ; Fundamental Research Funds for the Central Universities[JC2001] |
| WOS研究方向 | Mathematical & Computational Biology |
| 语种 | 英语 |
| 出版者 | HINDAWI LTD |
| WOS记录号 | WOS:000552737200001 |
| 源URL | [http://119.78.100.204/handle/2XEOYT63/15901]  |
| 专题 | 中国科学院计算技术研究所期刊论文_英文 |
| 通讯作者 | Chen, Jia-Wei; Gou, Shuiping |
| 作者单位 | 1.Xidian Univ, Sch Artificial Intelligence, Minist Educ, Key Lab Intelligent Percept & Image Understanding, Xian 710071, Peoples R China 2.Ankang Cent Hosp, Dept Infect Dis, Ankang 725000, Peoples R China 3.Chinese Acad Sci, Inst Comp Technol, Beijing 100190, Peoples R China 4.Guangdong Gen Hosp, Guangdong Prov Key Lab South China, Guangdong Acad Med Sci, Guangdong Cardiovasc Inst,Catheterizat Lab,Struct, Guangzhou 510000, Peoples R China 5.Guangdong Gen Hosp, Dept Cardiac Surg, Struct Heart Dis, Guangzhou 510000, Peoples R China |
| 推荐引用方式 GB/T 7714 | Lu, Yunfei,Li, Bing,Liu, Ningtao,et al. CT-TEE Image Registration for Surgical Navigation of Congenital Heart Disease Based on a Cycle Adversarial Network[J]. COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE,2020,2020:8. |
| APA | Lu, Yunfei.,Li, Bing.,Liu, Ningtao.,Chen, Jia-Wei.,Xiao, Li.,...&Zhuang, Jian.(2020).CT-TEE Image Registration for Surgical Navigation of Congenital Heart Disease Based on a Cycle Adversarial Network.COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE,2020,8. |
| MLA | Lu, Yunfei,et al."CT-TEE Image Registration for Surgical Navigation of Congenital Heart Disease Based on a Cycle Adversarial Network".COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE 2020(2020):8. |
入库方式： OAI收割
来源：计算技术研究所
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