DistortCorrect Stitcher: Microscopy Image Stitching with Integrated Optical Distortion Correction

The rapidly advancing field of imaging-based spatial transcriptomics demands microscopy images with larger fields of view (FOV) and high spatial resolution to accurately and efficiently quantify RNA molecules at the single-cell level. This challenge requires advanced image processing algorithms to s...

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Bibliographic Details
Published in:bioRxiv
Main Authors: Cang, Hu, Fan, Huaxun, Sun, Sha, Zhang, Kai
Format: Paper
Language:English
Published: Cold Spring Harbor Cold Spring Harbor Laboratory Press 03.11.2024
Cold Spring Harbor Laboratory
Edition:1.1
Subjects:
Bioinformatics
Image processing
Information processing
Integrated approach
Microscopes
Microscopy
RNA processing
Spatial discrimination
Transcriptomics
ISSN:2692-8205, 2692-8205
Online Access:Get full text
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Summary:The rapidly advancing field of imaging-based spatial transcriptomics demands microscopy images with larger fields of view (FOV) and high spatial resolution to accurately and efficiently quantify RNA molecules at the single-cell level. This challenge requires advanced image processing algorithms to seamlessly stitch multiple microscopic images while overcoming the inherent FOV limitations of microscopes. However, image stitching accuracy is often compromised by optical distortions, which are typically uncorrected or require cumbersome hardware-based calibration. Here, we present DistortCorrect Stitcher, a powerful software package that simultaneously estimates and corrects optical distortion during the stitching process. By iteratively integrating image stitching with distortion correction, our method significantly enhances alignment accuracy without relying on external calibration, providing a robust solution for processing spatial transcriptomics data. DistortCorrect Stitcher maintains high stitching fidelity across large tissue areas, ensuring that the molecular data remain reliable and biologically meaningful. This integrated approach has broad implications for improving spatial biology analysis and enabling more accurate high-throughput assays, thereby accelerating advancements in the field.Competing Interest StatementThe authors have declared no competing interest.
Bibliography:SourceType-Working Papers-1
ObjectType-Working Paper/Pre-Print-1
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Competing Interest Statement: The authors have declared no competing interest.
ISSN:2692-8205
2692-8205
DOI:10.1101/2024.10.28.620720