Edge Detection Algorithm for Magnetic Resonance Images Based on Multi-scale Morphology
Kim Wang, Jianhua Wu, Zhaoyu Pian, Guo Li, Liqun Gao · 2007
Medical image edge detection is an important work for object recognition of human organs and it is an important pre-processing step in medical image segmentation and 3D reconstruction. Conventionally, edge is detected according to some early brought forward algorithms such as gradient-based algorithm, but they are not so good for noise medical image edge detection. In this paper, based on multi-scale morphology algorithm is proposed to detect the edge of brain MRI with Gaussian and salt & pepper noise. Threshold is to classify the MRI into two opposite classes: object and background. The part which is larger than the threshold uses large-scale structure element to detect the edge, and uses small-scale structure element for the part less than the threshold. Large-scale structure element gets through small-scale structure element's dilation. The experimental results show that the proposed algorithm is more efficient for medical image denoising and edge detection than the usually used gradient-based edge detecting algorithms.