Abstract
BackgroundFurther advances in modern microscopy are leading to teravoxel-sized tiled 3D images at high resolution, thus increasing the dimension of the stitching problem of at least two orders of magnitude. The existing software solutions do not seem adequate to address the additional requirements arising from these datasets, such as the minimization of memory usage and the need to process just a small portion of data.ResultsWe propose a free and fully automated 3D Stitching tool designed to match the special requirements coming out of teravoxel-sized tiled microscopy images that is able to stitch them in a reasonable time even on workstations with limited resources. The tool was tested on teravoxel-sized whole mouse brain images with micrometer resolution and it was also compared with the state-of-the-art stitching tools on megavoxel-sized publicy available datasets. This comparison confirmed that the solutions we adopted are suited for stitching very large images and also perform well on datasets with different characteristics. Indeed, some of the algorithms embedded in other stitching tools could be easily integrated in our framework if they turned out to be more effective on other classes of images. To this purpose, we designed a software architecture which separates the strategies that use efficiently memory resources from the algorithms which may depend on the characteristics of the acquired images.ConclusionsTeraStitcher is a free tool that enables the stitching of Teravoxel-sized tiled microscopy images even on workstations with relatively limited resources of memory (<8 GB) and processing power. It exploits the knowledge of approximate tile positions and uses ad-hoc strategies and algorithms designed for such very large datasets. The produced images can be saved into a multiresolution representation to be efficiently retrieved and processed. We provide TeraStitcher both as standalone application and as plugin of the free software Vaa3D.
Highlights
Further advances in modern microscopy are leading to teravoxel-sized tiled 3D images at high resolution, increasing the dimension of the stitching problem of at least two orders of magnitude
In this table we report a comparison of displacement errors and quality measures between TeraStitcher and the state-of-the art stitching tools when stitching Megavoxel-sized datasets. aPublicly available dataset downloaded from http://www.vaa3d.org. bPublicly available dataset downloaded from http://www.xuvtools.org. cCLSM dataset
The results show that TeraStitcher can stitch both images acquired in Confocal Light Sheet Microscopy (CLSM) and images acquired with other microscopy techniques with single-pixel precision
Summary
We propose a free and fully automated 3D Stitching tool designed to match the special requirements coming out of teravoxel-sized tiled microscopy images that is able to stitch them in a reasonable time even on workstations with limited resources. The tool was tested on teravoxel-sized whole mouse brain images with micrometer resolution and it was compared with the state-of-the-art stitching tools on megavoxel-sized publicy available datasets. This comparison confirmed that the solutions we adopted are suited for stitching very large images and perform well on datasets with different characteristics. Some of the algorithms embedded in other stitching tools could be integrated in our framework if they turned out to be more effective on other classes of images To this purpose, we designed a software architecture which separates the strategies that use efficiently memory resources from the algorithms which may depend on the characteristics of the acquired images
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