Name
Title | ||
|---|---|---|
Parallel implementation of a nonrigid image registration algorithm for lung tumor boundary tracking in quasi real-time MRI |
Abstract | ||
|---|---|---|
This study presents an accelerated implementation of a two-dimensional moving mesh point correspondence algorithm using a GPU for tracking mobile tumor boundaries during radiation therapy. Normal CPU implementation of this algorithm is computationally intensive and time-consuming which limits its clinical utility, hence the need for a faster GPU implementation. One of the computationally intensive parts of the registration algorithm involves numerically solving a partial differential equation. In this paper we demonstrate that the computational performance of the algorithms can be improved by utilizing a shared memory implementation on the GPU. Evaluations in comparison to 600 manually drawn contours showed that the proposed GPU-based tracking of the tumor boundaries yielded similar level of accuracy as the CPU based approach with improved computational efficiency. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/EMBC.2017.8036828 | 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) |
Keywords | Field | DocType |
Algorithms,Computer Graphics,Humans,Lung Neoplasms,Magnetic Resonance Imaging | Computer vision,Central processing unit,Shared memory,Computer science,Mesh point,Algorithm,Artificial intelligence,Quasi real time,Partial differential equation,Image registration | Conference |
Volume | ISSN | ISBN |
2017 | 1557-170X | 978-1-5090-2810-8 |
Citations | PageRank | References |
0 | 0.34 | 3 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Nazanin Tahmasebi | 1 | 1 | 1.36 |
| Boulanger, P. | 2 | 28 | 10.62 |
| Kumaradevan Punithakumar | 3 | 216 | 24.40 |