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An Adaptive Approach for Image Subtraction Zhifeng Wang , Yurong Xu , James Ford , Fillia S. Makedon , Zhenwu Zhuang , Ling Gao , Justin Department of Computer Science, Dartmouth College, Hanover NH 03755, USA Advanced Imaging Center, Dartmouth Hitchcock Medical Center, Lebanon NH 03756, USA Abstract Image subtraction is widely used in angiography as a means of highlighting differences induced by contrast agents. New knowledge of previously unsuspected causes of disease, in particular, secondhand smoke exposure, spurs interest in pushing the limits of early accurate diagnosis. Simple image subtraction induces artifacts causing problems for ensuing measurements and 3D reconstruction. Image registration techniques have been used to partially solve this problem. However, a complete registration is slow, and misregistration often occurs in images where bones are surrounded by vessels with similar image characteristics. In this paper, we propose an approach based on the idea of global match followed by local an image pair is aligned using refinements. In the global match,a similarity measure so as to reduce overall difference. In the local refinements, localized displacements and deformations of tissue are handled by a combination of techniques: image registration, region growing, erosion, and dilation. This approach is fast compared to registration based image subtraction and it can find vessels abutting a bone. It is designed to be especially suitable for large cross-section image stacks. With additional vessel connectivity analysis between adjacent slices, the algorithm provides a good foundation for 3D vessel reconstruction. Keywords：Image subtraction, image registration, region growing, erosion, dilation, similarity measure, scattergram I. INTRODUCTION Image subtraction is a way to discover differences between images. It has many applications in medical image processing, especially in angiography: in this application, one image taken after injection