Primitive Simultaneous Optimization of Similarity Metrics for Image Registration
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Abstract (arXiv)
Even though simultaneous optimization of similarity metrics is a standard procedure in the field of semantic segmentation, surprisingly, this is much less established for image registration. To help closing this gap in the literature, we investigate in a complex multi-modal 3D setting whether simultaneous optimization of registration metrics, here implemented by means of primitive summation, can benefit image registration. We evaluate two challenging datasets containing collections of pre- to post-operative and pre- to intra-operative MR images of glioma. Employing the proposed optimization, we demonstrate improved registration accuracy in terms of TRE on expert neuroradiologists' landmark annotations.
Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 14 of its 29 references that are in the map. First posted on arXiv 4 Apr 2023.
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14 of 29 references.
References · 14
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Citing papers per year: 2026: 1.
1 paper.