Adaptive Segmentation of MR Axial Brain Images Using Connected Components

The role of connected components and connected filters is well established. In this paper a new segmentation procedure is presented based on connected components and connected filters. The use of connected components simplified the development of the algorithm. Moreover, if connected components are available as a basic data type, implementation is achievable without resorting to pixel level processing. Using parallel platforms with hardware support for connected components, the algorithm can fully exploit its data parallel implementation. We apply our segmentation procedure to axially oriented magnetic resonance brain images. Novel ideas are presented of how connected components operations (e.g. moments and bounding boxes) and connected filtering (e.g. area close-opening) can be effectively used together.