µCodes: A Universal Grid Platform for Microscale Mapping, Microscopy Navigation, and Multimodal Imaging

Different imaging modalities provide unique and valuable insights into biological sample characterizations. Integration of multimodal imaging techniques is essential for comprehensive biological sample analysis. µCodes, a microgrid system designed to enhance sample navigation, alignment, and co-registration of images obtained from various optical and electron microscopy techniques, is presented. µCodes is a platform for tracking and locating targets or cells of interest across different imaging modalities with high precision. In this paper, the design, fabrication, and implementation of µCodes are demonstrated, emphasizing their utility in imaging workflows for biological samples.

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Publication Details

Journal
Small
Published
2025-08-21
DOI
https://doi.org/10.1002/smll.202506183
Primary Topic
Cell Image Analysis Techniques
Type
article
Field-Weighted Citation Impact
0.00
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article

µCodes: A Universal Grid Platform for Microscale Mapping, Microscopy Navigation, and Multimodal Imaging

Stephen Nick Housley, Aref Valipour, Jae Du Ha
Small
Cell Image Analysis Techniques
article

µCodes: A Universal Grid Platform for Microscale Mapping, Microscopy Navigation, and Multimodal Imaging

Stephen Nick Housley, Aref Valipour, Jae Du Ha
article en

Abstract

Different imaging modalities provide unique and valuable insights into biological sample characterizations. Integration of multimodal imaging techniques is essential for comprehensive biological sample analysis. µCodes, a microgrid system designed to enhance sample navigation, alignment, and co-registration of images obtained from various optical and electron microscopy techniques, is presented. µCodes is a platform for tracking and locating targets or cells of interest across different imaging modalities with high precision. In this paper, the design, fabrication, and implementation of µCodes are demonstrated, emphasizing their utility in imaging workflows for biological samples.

SmallVol. 21(51)
Georgia Institute of Technology (US), Emory University (US)
Openalex Percentile: Top 85%
Cell Image Analysis Techniques
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