In this paper, based on the ideas of image texture analysis and motion tracking, we present a new method for left ventricular (LV) strain analysis from cine magnetic resonance images(MRI). First, the marking points are extracted with the Harris corner detector on or close to the endocardium and epicardium. Second, using the tree-structured wavelet algorithm, the corresponding marking points are matched automatically and the sparse displacement field is calculated precisely between the consecutive frames. Next, applying radial point interpolation with polynomial basis functions, which is used in the meshfree method, the dense displacement field is interpolated. Finally, LV strains is analyzed. The experimental results show that our method is feasible and effective. In this paper, we present a new method for LV strain analy- sis from cine MRI. First, the marking points are extracted with the Harris corner detector on or close to the endocardium and epicardium. Then, using the tree-structured wavelet algorithm, the corresponding marking points are matched automatically and the sparse displacement field is calculated precisely be- tween the consecutive frames. Next, applying radial point interpolation with polynomial basis functions, which is used in the meshfree method, the dense displacement field is inter- polated. Finally, LV strain is analyzed. The main advantages of the proposed method in this paper include: (1) The Harris corner detector is a popular interest point detector due to its strong invariance to: rotation, scale, illumination variation and image noise. Therefore, the extracted marking points are more accurate. (2) Taking advantage of the wavelet-based attribute vector (WAV)'s rotationl-invariance and uniqueness, the corresponding marking points are matched automatically. (3) Radial point interpolation with polynomial basis functions method has lower computational cost, high accuracy, and the Kronecker Delta function property, and can ensure the dense displacement field being continuous. (4) Compared with the existing methods estimating the dense displacement directly, the proposed method in this paper has lower computational cost. (5) It is desirable that our method only needs to preseg- ment the myocardium in the reference frame, and will decrease the complexity of operation. The rest of this paper is organized as follows. In Section II, related preliminary is briefly reviewed. In Section III, the proposed method is described in detail. In Section IV, an experiment is given to illustrate that our method is feasible. In Section V, the conclusion is given.
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