In this work, we introduce a fast and accurate method for unsupervised 3D medical image registration. This work is built on top of recent algorithm self-supervised anatomical embedding (SAM), which capable computing dense anatomical/semantic correspondences between two images at the pixel level. Our named SAM-enhanced registration (SAME), breaks down into three steps: affine transformation, coa...