Universal Drift Correction for Multidimensional Scanning Microscopy
Abstract
In scanning microscopy, drift causes the specimen to be sampled at positions displaced from the nominal probe positions. This displacement alters the spatial assignment of the recorded signals and biases quantitative measurements across two-dimensional imaging, channel-resolved spectroscopic mapping, and scan-position-resolved diffraction analysis. Here, we extend orthogonal-scan drift correction from 2D images to spectrum images and diffraction datasets. We demonstrate how to recover probe positions using either differently oriented multidimensional scans or structural reference images. The recovered positions are used either to resample the multidimensional data onto a regular grid or to assign each recorded signal to its corrected coordinate. Our method combines affine and non-rigid correction, requires no prior structural model, and is implemented as open-source, GPU-accelerated software that reduces processing times by two to three orders of magnitude, enabling routine and automated drift correction for quantitative multidimensional microscopy.
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BibTeX
@misc{lee2026universal,
title = {{Universal Drift Correction for Multidimensional Scanning Microscopy}},
author = {Sangjoon Lee and William Millsaps and Dasol Yoon and Caitlyn Obrero and Guoliang Hu and Corrie Barnes and Cedric Lim and Andrew Barnum and Arthur R. C. McCray and Colin Ophus},
howpublished = {arXiv},
year = {2026},
month = sep,
doi = {10.48550/arxiv.2609.30866},
eprint = {2609.30866},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2609.30866},
note = {CC BY 4.0},
}
RIS
TY - UNPB
TI - Universal Drift Correction for Multidimensional Scanning Microscopy
AU - Sangjoon Lee
AU - William Millsaps
AU - Dasol Yoon
AU - Caitlyn Obrero
AU - Guoliang Hu
AU - Corrie Barnes
AU - Cedric Lim
AU - Andrew Barnum
AU - Arthur R. C. McCray
AU - Colin Ophus
PY - 2026
DA - 2026/09/25
PB - arXiv
DO - 10.48550/arxiv.2609.30866
UR - https://arxiv.org/abs/2609.30866
AB - In scanning microscopy, drift causes the specimen to be sampled at positions displaced from the nominal probe positions. This displacement alters the spatial assignment of the recorded signals and biases quantitative measurements across two-dimensional imaging, channel-resolved spectroscopic mapping, and scan-position-resolved diffraction analysis. Here, we extend orthogonal-scan drift correction from 2D images to spectrum images and diffraction datasets. We demonstrate how to recover probe positions using either differently oriented multidimensional scans or structural reference images. The recovered positions are used either to resample the multidimensional data onto a regular grid or to assign each recorded signal to its corrected coordinate. Our method combines affine and non-rigid correction, requires no prior structural model, and is implemented as open-source, GPU-accelerated software that reduces processing times by two to three orders of magnitude, enabling routine and automated drift correction for quantitative multidimensional microscopy.
ER -