Medical image edge detection method based on adaptive facet model

Edge detection is one of the most important elements in medical image processing. This paper presents an adaptive facet model-based edge detection algorithm(A-facet). The size, form and direction of the moving window for facet fitting is adaptively steered by image local anisotropic features. Performance comparison is carried out between the proposed adaptive facet algorithm and the frequently used edge detection methods, including the classical Canny detector, Prewitt detector, Roberts and Log's methods. The results from experiments on simulated and real images demonstrate that the extracted edges can accurately represent the internal detail information, and the performance of anti-noise is obviously better than the classical methods.