Characterizing of region shapes in digital images is a common requirement in medical image processing. This paper describes an approach based on successive traversals around the region boundary, enabling a sequence of related shape information at different scales to be constructed. The approach is useful in that it allows several different shape characteristics to be determined using the same set of data. The approach and its implementation is described, and an example of its application to a problem in bio-medical cell discrimination is considered and compared with results from more conventional shape characterization techniques.
A wavelet-based multiscale scheme for segmenting MR images is presented, which aims to extract structures of different sizes by performing segmentation from coarse to fine scales. This scheme alleviates some common difficulties encountered by region-based segmentation to avoid over-segmentation as well as to prevent small regions from being missed. It also allows users more effective control over the segmentation process in order to extract features suitable for their own purposes.