3D multimodal cardiac data reconstruction using angiography and computerized tomographic angiography registration

• Main Authors: Al-Surmi, A. (Author), Dimon, M.Z (Author), Khalid, F. (Author), Mazaheri, S. (Author), Moosavi Tayebi, R. (Author), Sulaiman, P.S.B (Author), Wirza, R. (Author)
• Format: Article
• Language: English
• Published: BioMed Central Ltd. 2015
• Subjects: 3D reconstruction; algorithm; Algorithms; angiocardiography; Angiography; computer assisted tomography; Computerized tomography angiography; Coronary Angiography; coronary artery disease; Coronary Artery Disease; Coronary Stenosis; human; Humans; Imaging, Three-Dimensional; Labeling; multimodal imaging; Multimodal Imaging; Multimodal registration; procedures; radiography; Segmentation; sensitivity and specificity; Sensitivity and Specificity; three dimensional imaging; Tomography, X-Ray Computed
• Online Access: View Fulltext in Publisher; View in Scopus

 Background: Computerized tomographic angiography (3D data representing the coronary arteries) and X-ray angiography (2D X-ray image sequences providing information about coronary arteries and their stenosis) are standard and popular assessment tools utilized for medical diagnosis of coronary artery diseases. At present, the results of both modalities are individually analyzed by specialists and it is difficult for them to mentally connect the details of these two techniques. The aim of this work is to assist medical diagnosis by providing specialists with the relationship between computerized tomographic angiography and X-ray angiography. Methods: In this study, coronary arteries from two modalities are registered in order to create a 3D reconstruction of the stenosis position. The proposed method starts with coronary artery segmentation and labeling for both modalities. Then, stenosis and relevant labeled artery in X-ray angiography image are marked by a specialist. Proper control points for the marked artery in both modalities are automatically detected and normalized. Then, a geometrical transformation function is computed using these control points. Finally, this function is utilized to register the marked artery from the X-ray angiography image on the computerized tomographic angiography and get the 3D position of the stenosis lesion. Results: The result is a 3D informative model consisting of stenosis and coronary arteries' information from the X-ray angiography and computerized tomographic angiography modalities. The results of the proposed method for coronary artery segmentation, labeling and 3D reconstruction are evaluated and validated on the dataset containing both modalities. Conclusions: The advantage of this method is to aid specialists to determine a visual relationship between the correspondent coronary arteries from two modalities and also set up a connection between stenosis points from an X-ray angiography along with their 3D positions on the coronary arteries from computerized tomographic angiography. Moreover, another benefit of this work is that the medical acquisition standards remain unchanged, which means that no calibration in the acquisition devices is required. It can be applied on most computerized tomographic angiography and angiography devices. © 2015 Moosavi Tayebi et al.