New Methods of MR Image Intensity Standardization Via Generalized Scale

摘要

Image intensity standardization is a post-acquisition processing operation designed for correcting acquisition-to-acquisition signal intensity variations (non-standardness) inherent in Magnetic Resonance (MR) images. While existing standardization methods based on histogram landmarks have been shown to produce a significant gain in the similarity of resulting image intensities, their weakness is that, in some instances the same histogram-based landmark may represent one tissue, while in other cases it may represent different tissues. This is often true for diseased or abnormal patient studies in which significant changes in the image intensity characteristics may occur. In an attempt to overcome this problem, in this paper, we present two new intensity standardization methods based on the concept of generalized scale. In we introduced the concept of generalized scale (g-scale) to overcome the shape, topological, and anisotropic constraints imposed by other local morphometric scale models. Roughly speaking, the g-scale of a voxel in a scene was defined as the largest set of voxels connected to the voxel that satisfy some homogeneity criterion. We subsequently formulated a variant of the generalized scale notion, referred to as generalized ball scale (g_B-scale), which, in addition to having the advantages of g-scale, also has superior noise resistance properties. These scale concepts are utilized in this paper to accurately determine principal tissue regions within MR images, and landmarks derived from these regions are used to perform intensity standardization. The new methods were qualitatively and quantitatively evaluated on a total of 67 clinical 3D MR images corresponding to four different protocols and to normal, Multiple Sclerosis (MS), and brain tumor patient studies. The generalized scale-based methods were found to be better than the existing methods, with a significant improvement observed for severely diseased and abnormal patient studies.