A new image registration technique with free boundary constraints: application to mammography
Computer Vision and Image Understanding - Special issue on nonrigid image registration
The best-so-far selection in Artificial Bee Colony algorithm
Applied Soft Computing
Mutual information refinement for flash-no-flash image alignment
ACIVS'11 Proceedings of the 13th international conference on Advanced concepts for intelligent vision systems
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Spatial alignment of image data is a common task in computer vision and medical imaging. This should preferentially be done with minimal intervention of an operator. Similarity measures with origin in the information theory such as mutual information (MI) have proven to be robust registration criteria for this purpose. Intra-oral radiographs can be considered images of piecewise rigid objects. Teeth and jaws are rigid but can be displaced with respect to each other. Therefore MI criteria combined with affine deformations tend to fail, when teeth and jaws move with respect to each other between image acquisitions. In this paper, we consider a focused weighing of pixels in the reference image. The resulting criterion, focused mutual information (FMI) is an adequate tool for the registration of rigid parts of a scene. We also show that the use of FMI is more robust for the subtraction of lateral radiographs of teeth, than MI confined to a region of interest. Furthermore, the criterion allows the follow-up of small carious lesions when upper and lower jaw moved between the acquisition of test and reference image.