Carotid atherosclerosis plaque is the primary cause of heart disease and stroke. Thus

accurate identification of plaque component is the main basis for plaque rupture prediction. However

multiple sequence MR images are hampered by noise and misalignment. To solve the first problem

an improved denoising method based on wavelet transformation is used. Then

a registration method based on shape context method is proposed to accurately align multiple MR image sequence. We replace the traditional threshold function used in wavelet transform denoising with an adaptive threshold value that changes according to noise distribution in high-and low-frequency subband to achieve effective MRI denoising capabilities. Multiple MRI registration is performed by first identifying edge points with matching shape context. Then

an iterative procedure is invoked to obtain deformation field

which determines B-spline interpolated output image. The proposed denoising method is proved to remove image noise effectively while preserving original information. The overlapping accuracy among multiple sequences of the same artery reaches 96%±0.8%. Results from the experiment show the effectiveness of the proposed method at enhancing image quality.