NRStitcher: non-rigid stitching of terapixel-scale volumetric images


Loading...

Date

2019-12

Publication Type

Journal Article

ETH Bibliography

yes

Citations

Altmetric

Data

Abstract

In modern microscopy, the field of view is often increased by obtaining an image mosaic, where multiple sub-images are taken side-by-side and combined post-acquisition. Mosaic imaging often leads to long imaging times that can increase the probability of sample deformation during the acquisition due to, e.g. changes in the environment, damage caused by the radiation used to probe the sample or biologically induced deterioration. Here we propose a technique, based on local phase correlation, to detect the deformations and construct an artifact-free image mosaic from deformed sub-images. The implementation of the method supports distributed computing and can be used to generate teravoxel-size mosaics. We demonstrate its capabilities by assembling a 5.6 teravoxel tomographic image mosaic of microvasculature in whole mouse brain. The method is compared to existing rigid stitching implementations designed for very large datasets, and observed to create artifact-free image mosaics in comparable runtime with the same hardware resources.

Publication status

published

Editor

Book title

Volume

35 (24)

Pages / Article No.

5290 - 5297

Publisher

Oxford University Press

Event

Edition / version

Methods

Software

Geographic location

Date collected

Date created

Subject

Organisational unit

03817 - Stampanoni, Marco F.M. / Stampanoni, Marco F.M. check_circle

Notes

It was possible to publish this article open access thanks to a Swiss National Licence with the publisher.

Funding

135550 - In-vivo study of lung physiology with sub-second X-ray tomographic microscopy (SNF)

Related publications and datasets