Contour Extraction from IVUS Images Based on GVF Snakes and Wavelet Transform

The extraction of luminal borders (contours) from intravascular ultrasound (IVUS) images is helpful for the diagnosis of coronary artery diseases. A novel scheme for contour extraction is proposed in this paper, based on GVF snakes and wavelet transform. To solve the two difficulties of the traditional GVF snake, i.e. the contour initialization and the suppression of noise and artifact interference, there are two improvements in our proposed scheme. First, the procedure is made into full automation, with adopting the characteristics of the image sequences to produce an initial contour. Secondly, the robustness of the algorithm is enhanced, since the GVF snake is combined with discrete wavelet transform to deform the contour in multiscale images. The proposed scheme is verified on both the synthetic images and real IVUS images. The results show that this scheme is superior to traditional GVF snake in terms of boundary localization.