ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
IEEE Transactions on Information Technology in Biomedicine
IEEE Transactions on Information Technology in Biomedicine
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This paper presents a robust and fully automated registration algorithm for registration of images of Quadrature Tomographic Microscopy (QTM), which is an optical interferometer. The need for registration of such images is to recognize distinguishing features of viable embryos to advance the technique for In Vitro Fertilization. QTM images a sample (live embryo) multiple times with different hardware configurations, each in turn producing 4 images taken by 4 CCD cameras simultaneously. Embryo movement is often present between imaging. Our algorithm handles camera calibration1 of multiple cameras using a variant of ICP, and elimination of embryo movement using a hybrid of feature- and intensity-based methods. The algorithm is tested on 20 live mouse embryos containing various cell numbers between 8 and 26. No failure thus far, and the average alignment error is 0.09 pixels, corresponding to the range of 639 and 675 nanometers.