Understanding living cells and their processes requires analysis of data from various imaging systems and modalities that all use different file formats. Each experimental setup can represent a unique challenge to process the data. Multi-scale dynamic processes require tracking of various sized objects, from diffraction-limited particles to entire cells. There can be a few dozen to tens of thousands objects in each data set. In addition, intracellular processes are supported by sub-cellular structures that also need to be identified and quantified.
Thermo Scientific Amira Software provides a comprehensive array of tools for the flexible and accurate analysis of time series data of cellular processes. It enables researchers to perform dedicated segmentation workflows on their intra- and intercellular images and apply powerful automated object tracking solution.
To better understand embryonic development and how congenital disorders occur, scientists need to follow individual cells during the development cycle of an embryo. Using powerful, high-speed light-sheet microscopy, researchers are able to image these cells at sufficient temporal and spatial resolution.
With Amira Software, researchers are now able to deploy custom segmentation algorithms to segment each individual cell in a time series of images. These thousands of segmented cells can then be tracked using Amira Software's automated powerful tracking solution (powered by u-track 3D , under submission for peer-review from the Danuser Lab). With Amira automatic selection of the appropriate motion model, event detection, and gap closing, researchers can track thousands of fast-moving cells with high precision.
From these tracks, Amira Software enables scientists to extract quantitative information such as shape size and intensity parameters or measurements related to motility and diffusion. Researchers can also analyze the track across multiple cell generations to obtain cell lineage information.
With recent developments in light-sheet microscopy, researchers are now able to image intracellular particles at extraordinary spatial and temporal resolution. Intracellular processes such as membrane dynamics, viral infections, intracellular transport, and gene transcription can now be studied with greater accuracy. The potential for such accuracy leads to the desire of scientists to track these particles, which could represent single molecules or macromolecular complexes, organelles, viruses, or microspheres.
Amira Software enables detection of these particles in the most commonly used experimental setups. Researchers can allow Amira Software choose the best motion model for each individual particle and time step.
Analysis of filaments and microtubules is of great interest when studying intracellular processes, composition of cellular structure, and cell migration. Studying these cellular structures will lead to the development of disease treatments.
With Amira Software, researchers are able to use a template-matching algorithm to automatically detect and trace these fine filaments in noisy Cryo-EM or DualBeam data. In addition, Amira Software enables scientists to reconstruct filamentous networks and edit the resulting graphs to remove image features erroneously identified as filaments or to add missing parts of a network. Graphs of filaments can then be quantified by measuring parameters such as amount, length, thickness, orientation, ranks, etc. Compelling 3D renderings can be created from the reconstructed model and the computed parameters. The Max Planck Institute of Neurobiology uses Amira Software for axon tracing.
Researchers working with fluorescence light microscopes often acquire data with multiple channels. Each channel may highlight different proteins or molecules with fluorescent stains that emit light at various wavelengths. Scientists then face difficulties combining all channels to develop workflows to extract the desired information needed for obtaining quantitative results for their analysis.
Amira graphical workflow design tools, combined with a comprehensive image processing toolbox, allows researchers to solve this problem and compute the quantitative information that is needed for cutting edge research. They can then communicate these workflows and results to peers as screenshots or animations using Amira Software’s professional visualization tools.
Morphological analysis of the organ of Corti (in section of murine cochlea).
Data is courtesy of Decibel Therapeutics
Video: ~5 min.
Cellular spheroids are 3D cell cultures that represent in vivo tissue better than traditional cellular monolayers, improving the ability of researchers to study cancer, diabetes mellitus, or stem cells among many applications. However, cell analysis in such 3D multicellular objects is not accurately possible, especially without destroying the object of study.
Amira Software can automatically separate the cells and perform volumetric, morphometric, and intensity measurements on individual cells and their nuclei in 3D image data of these spheroids – as demonstrated in this animation. Amira Software also helps researchers with the analysis of conventional 2D cellular monolayers.
Data is courtesy of Dr. Matthias Meier, IMTEK, University of Freiburg.
The main challenge in CLEM workflows appears during the sample preparation and image acquisition step, when microscopists are transferring the sample from a physiological state to a cryo-sample for electron microscopy. Once this experimental challenge has been overcome, the next difficulty is finding a good solution to fuse the multi-channel time series data from the light microscope with the structural still image from the electron microscope. To support this image processing workflow, the software tools need to support handling of multiple volumes, registering these volumes, correlating measurements, and visualizing the multi-modal data in the same 3D space for image fusion.
With its long-standing applications in multi-modality imaging techniques, Amira Software is the tool of choice for many researchers working with data from different imaging modalities. Amira architecture supports multi-volume data processing and visualization from the ground up. The automatic registration tools integrated into the standard edition of Amira Software with the Multi-Planar Workroom offer the flexibility of the most commonly used automated registration metrics and optimizers that allow for the adjustment of the registration parameters to meet the needs of your data. Whatever the experimental challenges that CLEM researchers have to overcome, Amira Software is ready for their data.
The present testimonial highlights the way Amira Software supported Matthia A. Karreman, MSc, PhD at EMBL and DKFZ, Heidelberg, Germany, in her project on multimodal correlative microscopy to efficiently target single tumor cells in vivo. Read reference paper.
Video: 6 min
Studying the molecular machinery of cells from atomic details to the cellular context is challenging for structural and cell biologists. Progress has been made in unraveling the structures of individual proteins and protein complexes using single particle analysis (SPA), a cryo-electron microscopy (cryo-EM) workflow, which has turned 3D reconstructions of protein complexes into a routine technique. However, while SPA solves the structure of highly purified proteins, another cryo-EM method, cryo-electron tomography (cryo-ET) opens 3D windows into cells, allowing a molecular view of proteins in their native environment. One drawback is that traditional methods of manual segmentation of cryo-tomograms are extremely time-consuming, and the final visualization can still be sub-par.
Amira Software accelerates segmentation by employing automated detection of cellular features, such as filaments and membranes. By performing advanced image analysis and statistics on the cryo-tomograms, Amira Software combines data from these individual structures, averaging out noise and increasing contrast to create a composite model with higher resolution.
With the large variety of imaging techniques available to study inter- and intracellular processes, scientists are often confronted with image equipment from various vendors all preferring their own proprietary file format. This can complicate the image analysis and visualization task.
Amira Software makes this task easy. Through the use of the XBioFormats extension, scientists can conveniently load 3D or 4D+ data from over 150 file formats. This allows them to immediately work with their data in a single application without the need to export data to a common file format.
For data sets that exceed the available hardware memory, Amira Software converts your large data to the LDM format directly from the Bio-Formats
Amira Software integrates a ready-to-use custom Python distribution that includes the most commonly used scientific packages from the Python eco-system. This allows the seamless creation of script objects using Python utilities that can later be attached to data objects in the Amira Software graphical user interface.
The main benefits of Python for Amira-Avizo Software are:
Amira Software for Cell Biology Edition is a superset of Amira Software, bundling new and added-value extensions, and is available as a stand-alone new license, or through a specific upgrade program to existing users of Amira Software.
*For Research Use Only. Not for use in diagnostic procedures.