Needles & Haystacks: Dataset and Benchmark for Domain-Agnostic Image-Based Rigid Slice-to-Volume Registration

Anton Frolov, Florian Kleiner, Christiane Rößler, Volker Rodehorst; Proceedings of the Winter Conference on Applications of Computer Vision (WACV), 2025, pp. 7081-7091

We address domain-agnostic slice-to-volume (S2V) registration the alignment of 2D sliced/tomographic images into 3D volumes without prior knowledge of structure shape or orientation. While S2V registration is well-studied in medical imaging which often relies on auxiliary information (e.g. landmarks segmentation masks pre-defined orientations canonical/atlas volumes) applications such as micro-structure characterization in materials science lack such domain-specific aids. This leaves the task inherently ill-posed due to noise unstructured regions repetitive patterns rotational and translational symmetries. To address this challenge we present "Needles & Haystacks" a novel multi-domain algorithm development dataset with 158436 unique registration problems and ground-truth solutions based on diverse and openly licensed real-world volumetric data. Additionally we provide an online platform with 8461 test problems for reproducible evaluation of competing methods. We also propose strong baseline solutions with public implementations and highlight opportunities for further algorithmic advancements.