AI Insight
The Robust Non-rigid Registration Challenge for Expansion Microscopy (RnR-ExM) was created to benchmark three-dimensional registration algorithms on challenging real-world ExM datasets. The challenge released 24 pairs of high-resolution 3D volumes from zebrafish, mouse, and C. elegans, with curated segmentation masks and synthetic training data to facilitate algorithm development. Six teams submitted solutions by the deadline, with the top three presenting at ISBI 2023, demonstrating current capabilities in aligning expanded biological samples.
Why it matters
Accurate registration of ExM volumes is critical for multiplexed molecular mapping and cell-type-specific structural profiling in biological research. This challenge establishes a standardized benchmark for evaluating registration methods and provides open datasets and code that can advance the development of better alignment algorithms for nanoscale biological imaging.
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⚠️ Preprint – Noch nicht peer-reviewed
Dieser Artikel wurde noch nicht von unabhängigen Experten begutachtet. Die Ergebnisse sind vorläufig und sollten mit Vorsicht interpretiert werden.
Expansion Microscopy (ExM) enables nanoscale imaging of biological samples while preserving structural and molecular details. The Robust Non-rigid Registration Challenge for ExM (RnR-ExM) was launched to benchmark 3D registration algorithms on real-world ExM datasets. The challenge released 24 pairs of high-resolution 3D volumes from zebrafish, mouse, and C.~elegans, deliberately selected for their difficulty with standard alignment methods. To evaluate performance, we provided curated segmentation masks of nuclei and blood vessels as landmarks for half of the dataset. To encourage learning-based approaches, we released code for generating synthetic training data reflecting the deformation and appearance of the unlabeled pairs. By submission, 168 participants registered, with six teams submitting results by the deadline; the top three were invited to present at ISBI 2023. Accurate registration of ExM volumes is essential for downstream biological analyses such as multiplexed molecular mapping and cell-type-specific structural profiling. In this paper, we detail the methods and results of these top teams, highlighting current capabilities and future directions for 3D registration in ExM. All datasets and code are available at https://rnr-exm.grand-challenge.org/
Source: RnR-ExM: Robust Non-rigid Registration Challenge for Expansion Microscopy Volumes