Temporally diffeomorphic cardiac motion estimation from three‐dimensional echocardiography by minimization of intensity consistency error. Issue 5 (15th April 2014)

• Record Type: Journal Article
• Authors: Zhang, Zhijun; Ashraf, Muhammad; Sahn, David J.; Song, Xubo
• Is Part Of: Medical physics. Volume 41:Issue 5(2014)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2014-04-15
• Subjects: Ultrasonography -- Numerical optimization -- Artifacts and distortion -- Noise; deformation -- echocardiography -- gradient methods -- image denoising -- image sequences -- medical image processing -- minimisation -- motion estimation -- phantoms; cardiac motion estimation -- diffeomorphic registration -- echocardiography; Echo‐tomography -- Biological material, e.g. blood, urine; Haemocytometers -- Digital computing or data processing equipment or methods, specially adapted for specific applications -- Image data processing or generation, in general -- Image enhancement or restoration, e.g. from bit‐mapped to bit‐mapped creating a similar image -- Analysis of motion; Medical imaging -- Motion estimation -- Sequence analysis -- Heart -- Cardiac dynamics -- Heart disease -- Ice -- Three dimensional image processing -- Magnetic resonance imaging -- Decorrelation; Medical physics -- Periodicals; Medical physics; Geneeskunde; Natuurkunde; Toepassingen; Biophysics; Periodicals; Periodicals; Electronic journals; 610.153
• DOI: 10.1118/1.4867864
• Languages: English
• ISSNs: 0094-2405

Abstract

Abstract : Purpose: : Quantitative analysis of cardiac motion is important for evaluation of heart function. Three dimensional (3D) echocardiography is among the most frequently used imaging modalities for motion estimation because it is convenient, real‐time, low‐cost, and nonionizing. However, motion estimation from 3D echocardiographic sequences is still a challenging problem due to low image quality and image corruption by noise and artifacts. Methods: : The authors have developed a temporally diffeomorphic motion estimation approach in which the velocity field instead of the displacement field was optimized. The optimal velocity field optimizes a novel similarity function, which we call the intensity consistency error, defined as multiple consecutive frames evolving to each time point. The optimization problem is solved by using the steepest descent method. Results: : Experiments with simulated datasets, images of an ex vivo rabbit phantom, images of in vivo open‐chest pig hearts, and healthy human images were used to validate the authors' method. Simulated and real cardiac sequences tests showed that results in the authors' method are more accurate than other competing temporal diffeomorphic methods. Tests with sonomicrometry showed that the tracked crystal positions have good agreement with ground truth and the authors' method has higher accuracy than the temporal diffeomorphic free‐form deformation (TDFFD) method. Validation with an open‐access human cardiac dataset showed that the authors' method has smaller feature tracking errors than both TDFFD and frame‐to‐frame methods. Conclusions: : The authors proposed a diffeomorphic motion estimation method with temporal smoothness by constraining the velocity field to have maximum local intensity consistency within multiple consecutive frames. The estimated motion using the authors' method has good temporal consistency and is more accurate than other temporally diffeomorphic motion estimation methods.