Object Detection in Medical Images Based on Improved Morphological Multiresolution Decomposition and Morphological Segmentation

A semi-automatic object detection method based on mathematical morphology image processing techniques is presented. This paper does not present a complete methodology but rather an illustration of a potential application of mathematical morphology to medical images. The method based on mathematical morphology tools includes an improved multiresolution morphological decomposition algorithm (IMMD) and other morphological segmentation techniques. In IMMD, a group of openings by morphological reconstruction with different structuring elements permits a size-oriented object decomposition. Each image component contains objects with a limited size distribution, and the original image can be completely reconstructed by addition, from these decomposed images. Thus, specific methods can be employed separately on these image components for a better segmentation result. Image processing techniques based on mathematical morphology including morphological filtering, morphological gradient transform, dilation, hit/miss transform and so on, are employed in the segmentation procedures. In applications to object detection of various medical CT (Computer Tomography) and MR (Magnetic Resonance) images, fairly good results have been obtained which show that this approach bears higher degree of segmentation accuracy and consistency.