Name
Abstract | ||
|---|---|---|
Live three dimensional (3D) transesophageal echocardiography (TEE) provides real-time imaging of cardiac structure and function, and has been shown to be useful in interventional cardiac procedures. Its application in catheter based cardiac procedures is, however, limited by its limited field of view (FOV). In order to mitigate this limitation, we register pre-operative magnetic resonance (MR) images to live 3D TEE images. Conventional multimodal image registration techniques that use mutual information (MI) as the similarity measure use statistics from the entire image. In these cases, correct registration, however, may not coincide with the global maximum of MI metric. In order to address this problem, we present an automated registration algorithm that balances a combination global and local edge-based statistics. The weighted sum of global and local statistics is computed as the similarity measure, where the weights are decided based on the strength of the local statistics. Phantom validation experiments shows improved capture ranges when compared with conventional MI based methods. The proposed method provided robust results with accuracy better than 3 mm (5 degrees) in the range of -10 to 12 mm (-6 to 3 degrees), -14 to 12 mm (-6 to 6 degrees) and -16 to 6 mm (-6 to 3 degrees) in x-, y-, and z- axes respectively. We believe that the proposed registration method has the potential for real time intra-operative image fusion during percutaneous cardiac interventions. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1117/12.845425 | Proceedings of SPIE |
Keywords | Field | DocType |
Cardiac image-guided intervention,Image registration,Multimodal image registration,transesophageal echocardiography,Pre-operative MRI | Field of view,Computer vision,Similarity measure,Image fusion,Imaging phantom,Local statistics,Mutual information,Artificial intelligence,Image registration,Magnetic resonance imaging,Physics | Conference |
Volume | ISSN | Citations |
7625 | 0277-786X | 0 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jonghye Woo | 1 | 132 | 21.21 |
| Vijay Parthasarathy | 2 | 17 | 3.95 |
| dalal sandeep | 3 | 0 | 0.34 |
| ameet kumar jain | 4 | 25 | 6.16 |