Product Introduction

Selected Features, Use Cases and Modules for Advanced Image Analysis: ZEISS arivis Pro

Create Flexible Workflows to Answer Your Research Questions

26 August 2024 · 23 min read
  • Materials Sciences
  • Life Sciences
  • Laboratory Routine
Profile picture of Ofra Kleinberger Riedrich
Author Ofra Kleinberger Riedrich Content and Product Marketing (ZEISS arivis)
Abstract

Learn How Diverse Image Ananlysis Features Enable the Flexibility to Create Unique Workflows

Multiple features can be easily added together to create an advanced and automated image analysis pipeline that may answer your research questions. With ZEISS arivis Pro it is easy to create elaborate workflows and realize your unique image analysis requirements. The easy-to-use software allows for a clear understanding and usage of the diverse features to make up the required steps in your image analysis. Even beginners can create analysis pipelines, programming knowledge is not needed.

In this article, we introduce selected image analysis features and modules we and our customers have repeatedly found helpful for various research applications.

Imaging subcellular dynamics in multicellular organisms

These data were kindly provided by Tsung-Li Liu, Srigokul Upadlyayula, Tom Kirchhausen, and Eric Betzig and appear in their excellent paper: “Observing the cell in its native state: Imaging subcellular dynamics in multicellular organisms”.

Define Cell Boundaries with Membrane-based segmentation

Finding cell boundaries based on membrane-localized contrast is made many times easier by new algorithms that enhance membranes in 3D and an operator designed to segment cells in 3D. This workflow allows use of any image filters upstream of the Membrane-based Segmentation, which enables optimization of results and/or application to challenging images.

Users can select between Membrane Enhancement and Objectness Measure (sheets) filters depending on data quality and time constraints. Membrane Enhancement gives the highest quality but takes longer while Objectness Measure computes faster. The Membrane-based Segmentation is adjusted interactively to increase cell segmentation yield and “over splitting” is easily proof-edited with the Merge tool.

Segmented object directly viewed in the software

The measurements can be visualized in the 4D Viewer using a color code and exported to Excel or via CSV to any other program for further statistical analysis.

Measure Cell Volumes Using the Blob Finder

The Blob Finder analysis operator is ideal for segmenting cells or any other type of rounded cell organelles in a noisy image in an easy-to-use 3-step process. This function combines automatic seed finding based on structural information of an object map and a watershed algorithm. It is part of Analysis Pipeline, which allows for the easy segmentation and subsequent quantitative analysis of cells, spheroids, nuclei or any other type of rounded cell organelles, even in crowded and noisy environments in 2D, 3D and 4D data sets. This operator can be used without complex image processing beforehand, with integral watershed to correctly split objects even in a densely packed cluster.

Region growing image analysis viewed in 3D

Flexible Seeded Region Growing

The Seeded Region Growing Operation of ZEISS arivis Pro uses two different channels to achieve more precise segmentation results. In a simple two-step approach, you can choose one channel for seeding and another one for growing. You can easily segment whole cell bodies based on positive nuclear staining to easily separate close cells. The Watershed Operation for easy detection of non-roundish cells splits objects of any shape.

Create great results using any segmenter for seeding, using these as a starting point for Region Growing. Also, objects added into the data set via the VR Toolkit can be used for Region Growing. Use the new Splitting Operation as a modifier of segmentation objects to automatically split them in a pipeline run.

The ZEISS arivis Pro Tile Sorter Window

Tiling, Stitching and Alignment

Various applications require a process named stitching and alignment as a prerequisite step for the visualization of 3D or 4D volumetric files. Here, every plane of the resulting image is combined of a number of tiles acquired separately.

ZEISS arivis Pro is the unique tool for effective stitching and alignment of hundreds to thousands of multiple single files (tiles), which may create volumes of several hundred gigabyte or even terabyte in total file size. The arivis Pro Tile Sorter allows for a complete interactive adjustment for stitching.

Image Courtesy of vDisco technology, Ertürk Lab, Institute for Stroke and Dementia Research, Klinikum der Universität München, Munich, Germany.

Overcome Limitations of Volume Fusion

Some samples may be too large to be imaged in a single field of view at the desired resolution. Mosaic tiling can commonly workaround this limitation and the arivis Pro Tile Sorter can conveniently stitch such images into a single large volume. In some cases mosaic tiling may not be sufficient and it may be necessary to move/turn the sample to image the complete volume which can prevent stitching methods that rely on translation alone. The arivis Pro Volume Fusion Module overcomes these limitations and allows to fuse volumes based on landmarks and/or the free movement, rotation and scaling of a surface representation.

Distance measurement in 3D image analysis.

Diverse Tools for Relationship Identification and Analysis

The Colocalization operator is ideal for finding relationships between objects, in a one to any relationship.The enhanced Colocalization operator allows groups to be created from a reference (parent) and subjects (child) based on position, and finds relationships between them. As part of the analysis pipeline, it allows for the easy segmentation and subsequent quantitative analysis of cells, spheroids, nuclei or any other type of rounded cell organelles, even in crowded and noisy environments in 2D, 3D and 4D data sets.

The segment tracker operator is used for connecting moving objects in time, that is finding relationship of objects during a time course. This allows for sophisticated measurements of a group created between a reference (parent) and subjects (child) objects.
These two operators requires two groups of objects, references and subjects, to find relationships between the groups.

Distance measurements can be based on surface-surface or centroid-centroid calculations and included directly into your analysis pipeline to filter and categorize objects based on proximity. The distance filter also differentiates between positive and negative distances for objects outside or inside other objects respectively.

Courtesy of Dr. Carlo Beretta, Livia Asan, Dr. Johannes Knabbe and Prof. Dr. Thomas Kuner, Department of Functional Neuroanatomy, Heidelberg University.

Import and Export Imaging Data and Results

The Open Source community offers many special functionalities and regularly adds new ones to the research community. On the other hand many users prefer a commercial, robust and fully supported image analysis platform with a unified UI that covers all aspects of image processing, analysis and visualization of results via desktop workstation, cloud computing or Virtual Reality. Therefore an easy transition between open source/third party packages and our arivis Scientific Imaging Platform is essential. With the ZEISS arivis Pro Exchange Objects with Open Source module we offer an integrated solution to imaging facilities and PIs to connect with open source workflows as well as with any other software which is capable of exporting/importing labelled images. Easily interface with your specific workflows whenever you are using segmentation functions with open source packages such as Fiji, ImageJ, Ilastik, Python or with commercial solutions such as MATLAB.

Import resulting objects e.g. from Fiji or any other software in a single step into ZEISS arivis Pro (formerly Vision4D) and visualize the segmentation in 3D to create impressive movies with our arivis storyboard. This is a combined workflow using Ilastik autocontext, 3D segmentation using ImageJ-Matlab.

Automatic 3D neuron tracing of neuronal tissue (mouse brain) with ZEISS arivis Pro and ZEISS LSM 980 confocal microscope. Original 3D tissue volume dataset (45GB CZI, confocal fluorescence microscopy, single channel) kindly provided by Dr. Steffen Burgold, ZEISS RMS Customer Center Oberkochen, Germany.

Automatic Neuron Tracing and Trace Editing

The novel software architecture and algorithms of ZEISS arivis Pro deliver top performance in tracing applications for various imaging modalities in light microscopy. Combined with our best-in-class Machine Learning segmentation, automatic tracing and trace editing of multidimensional data sets becomes an easy task, without the need to be an expert in bioinformatics. ZEISS arivis Pro allows you to create expert results and meaningful output data for any kind of tracing data sets. The new semi-automatic trace editing tool creates a neuron trace or branch interactively by drawing in the viewer with automatic detection of the path. And the unique VR Toolkit gives you superior productivity when proofreading and correcting your automatically created results.

Adjustable Dragon Tail and Vector Display for Tracking and Lineage.

Dynamics, Tracking and Lineage

Tracking cells or subcellular particles in microscopic data can be challenging. The Tracking Module allows analysis of the movement of small (i.e. particle tracking) or large objects (e.g. nuclei, cells, organisms) over time in both 2D or 3D multichannel image sets of any size (100s of GBs or TBs). With ZEISS arivis Pro we offer an easy to use approach with full control and interactivity at all steps. The novel software architecture and algorithms deliver top performance on tracking analysis of complex biological data. Combined with our Machine Learning segmentation, tracking and lineage analysis of multidimensional data sets will become an easy task, without the need to be an expert in image analysis. ZEISS arivis Pro allows you to create expert results and meaningful output data for any kind of tracking or lineage data sets. A manual track tool creates a track or branch interactively in the viewer by placing spots (using markers or Magic Wand). Use the VR Toolkit to proofread and correct your automatically created results much more efficiently than ever before.


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