Biomedical imaging and analysis

Abstract

A method for synthesizing three dimensional multimodality image sets into a single composite image with accurate registration and congruence. Surfaces are initially extracted from two or more different images to be matched using semi-automatic segmentation techniques. These surfaces are represented as contours with common features to be matched. A distance transformation is performed for one surface image, and a cost function for the matching process is developed using the distance image. The geometric transformation includes three-dimensional translation, rotation and scaling to accommodate images of different position, orientation and size. The matching process involves efficiently searching this multi-parameter space and adjusting a surface or surfaces to find the best fit among them which minimizes the cost function. The local minima problem is addressed by using a large number of starting points. A pyramid multi-resolution approach is employed to speed up both the distance transformation computation and the multi-parameter minimization processes. Robustness in noise handling is accomplished using multiple thresholds embedded in the multi-resolution search. The method can register both partially overlapped and fragmented surfaces.