Vector Image Model to Object Boundary Detection in Noisy Images

A New model is designed for boundary
detection and applied it to object segmentation problem
in medical images. Our edge following technique
incorporates a vector image model and the edge map
information. The proposed technique was applied to
detect the object boundaries in several types of noisy
images where the ill-defined edges were encountered. The
proposed techniques performances on object
segmentation and computation time were evaluated by
comparing with the popular methods, i.e., the ACM, GVF
snake models. Several synthetic noisy images were
created and tested. The method is successfully tested in
different types of medical images including aortas in
cardiovascular MR images, and heart in CT images.