• Title of article

    Large-Deformation Image Registration of CT-TEE for Surgical Navigation of Congenital Heart Disease

  • Author/Authors

    Gou, Shuiping Xidian University - Xi’an, China , Chen, Linlin Xidian University - Xi’an, China , Gu, Yu Xidian University - Xi’an, China , Huang, Liyu Department of Biological Science and Engineering - Xidian University - Xi’an, China , Huang, Meiping Guangdong General Hospital - Guangdong Academy of Medical Sciences - Guangzhou, China , Zhuang, Jian Department of Cardiac Surgery - Guangdong Cardiovascular Institute - Guangdong Provincial Key Laboratory of South China Structural Heart Disease - Guangdong General Hospital - Guangdong Academy of Medical Sciences - Guangzhou, China

  • Pages
    11
  • From page
    1
  • To page
    11
  • Abstract
    Te surgical treatment of congenital heart disease requires navigational assistance with transesophageal echocardiography (TEE); however, TEE images are ofen difcult to interpret and provide very limited anatomical information. Registering preoperative CT images to intraoperative TEE images provides surgeons with richer and more useful anatomical information. Yet, CT and TEE images difer substantially in terms of scale and geometry. In the present research, we propose a novel method for the registration of CT and TEE images for navigation during surgical repair of large defects in patients with congenital heart disease. Valve data was used for the coarse registration to determine the basic location. Tis was followed by the use of an enhanced probability model map to overcome gray-level diferences between the two imaging modalities. Finally, the rapid optimization of mutual information was achieved by migrating parameters. Tis method was tested on a dataset of 240 images from 12 infant, children (≤ 3 years old), and adult patients with congenital heart disease. Compared to the “bronze standard” registration, the proposed method was more accurate with an average Dice coefcient of 0.91 and an average root mean square of target registration error of 1.2655 mm.
  • Keywords
    Large-Deformation , CT-TEE , TEE , CT
  • Journal title
    Computational and Mathematical Methods in Medicine
  • Serial Year
    2018
  • Record number

    2610362