Name
Title | ||
|---|---|---|
Automatic correction of motion artifacts in 4D left ventricle model reconstructed from MRI |
Abstract | ||
|---|---|---|
This paper describes a computer method to correct the shape of three-dimensional (3D) left ventricle (LV) models created from magnetic resonance imaging (MRI) data that is affected by patient motion during scanning. Three-dimensional meshes of the LV endocardial and epicardial surfaces are created from border-delineated MRI data at every time frame of the cardiac cycle to generate a time-series model of the heart. A geometrically-based approach is used to achieve smooth epicardial shapes by iterative in-plane translation of vertices in the LV model. The Principal Curvatures of the LV epicardial surfaces across multiple time frames are used to construct a shape-based optimization objective function to restore the shape of the LV via a dual-resolution semi-rigid deformation process and a free-form geometric deformation process. A limited memory quasi-Newton algorithm, L-BFGS-B, is then used to solve the optimization problem. We tested our algorithm on 9 patient-specific models and it was able to correct motion artifacts without altering the general shape of the heart, such as its asymmetrical shape. The magnitudes of in-plane translations (Δx = 0.972±0.857 mm and Δy = 1.306±1.290 mm in the x- and y-directions, respectively) are also within the range of published experimental findings. The average computational time to correct each 4D model is 6 min 34 s. |
Year | Venue | Keywords |
|---|---|---|
2014 | CinC | biomedical mri,cardiology,image reconstruction,medical image processing,motion compensation,optimisation,3d meshes,4d left ventricle model,lv endocardial surfaces,lv epicardial surfaces,mri reconstruction,principal curvatures,dual resolution semirigid deformation process,free form geometric deformation process,limited memory quasinewton algorithm,magnetic resonance imaging,motion artifacts automatic correction,optimization problem,patient motion,image restoration,biomedical imaging,optimization,shape |
Field | DocType | Volume |
Computer vision,Polygon mesh,Medical imaging,Principal curvature,Artificial intelligence,Deformation (mechanics),Image restoration,Cardiac cycle,Optimization problem,Mathematics,Magnetic resonance imaging | Conference | 41 |
ISSN | Citations | PageRank |
2325-8861 | 1 | 0.39 |
References | Authors | |
5 | 8 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Y. Su | 1 | 20 | 10.55 |
| mayling tan | 2 | 1 | 1.41 |
| chiwan lim | 3 | 1 | 0.39 |
| Soo Kng Teo | 4 | 14 | 6.97 |
| s selvaraj | 5 | 2 | 1.70 |
| Min Wan | 6 | 2 | 3.19 |
| Liang Zhong | 7 | 4 | 4.21 |
| Ru-San Tan | 8 | 239 | 22.37 |