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Amira for Neuroscience

3D visualization and analysis software

Studying the brain and neuro-functions requires the knowledge of a vast selection of experimental methods, from cell preparation to image acquisition and analysis.

Thermo Scientific™ Amira Software aims at supporting researchers in the most frequently used image analysis techniques, such as filament tracing and editing, DTI analysis, brain perfusion analysis, and object tracking.

Combining Amira Software's versatility, with state-of-the-art 3D visualization and image processing, enables researchers to create custom workflows that extract exactly the desired type of information from an image.

 

Application examples:





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Courtesy of Ali Ertück, Max Planck Institute of Neurobiology

Filament tracing and editing

Network analysis of neurons and other filamentous structures is of great interest to study and understand the morphology and remodeling capabilities of such networks. This further helps to create a greater understanding of brain functionality and disease impact and treatment. 

With Amira Software, our customers are able to trace, analyze and quantify 3D images of filamentous structures such as neurons, blood vessels and microtubules. Filamentous networks can be reconstructed, and measures such as length, thickness, orientation, ranks, etc. can be computed and visualized in compelling 3D renderings. Tracing can be performed automatically or interactively, depending on the application and needs. Our template matching algorithm allows automatic detection and tracing of fine filaments in noisy CryoEM data. Amira Software also enables scientists to edit the resulting graphs to remove image feature erroneously identified as a filament, or add missing parts of a network. 

The Max Planck Institute of Neurobiology uses Amira Software for axon tracing. 
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DTI analysis

Understanding the interconnectivity of the brain is essential for functional brain research. This allows researchers to better understand how different parts of the brain jointly orchestrate higher cognitive functions and motor-skills.

With Amira Software, our customers are able to perform the entire DTI analysis workflow by first converting images into Talairach coordinates. Scientists are then able to map multiple brain images onto a reference brain. Once, the brain images are aligned, gradient images can be converted into a tensor field, and finally nerve fiber bundles can be tracked and visualized with our state-of-the-are visualization tools. For convenience, researchers can automatically strip the skull and surrounding tissue from MRI brain data. 

Brain perfusion analysis

Brain perfusion studies help researchers and scientist to understand the impact of strokes or other brain tissue diseases such as Alzheimer and dementia. The exact location and duration of a stroke can determine functional impact of the event.

With Amira Software, our customers are able to analyze brain perfusion in perfusion weighted MRI and CT images. This analysis includes computation of mean transit time (MTT), cerebral blood flow (CBF), and cerebral blood volume (CBV). 

Object tracking

In Neuroscience, tracking of objects such as neurons in developing embryos, neurotransmitters, and receptors allow scientist to further understand intra- and inter-cellular processes in the brain.

With Amira Software, our customers are able to track single-cells or single-particles in various types of 3D images. It enables scientist to create their own custom segmentation workflow to detect their objects of interest. These objects can then be tracked using state-of-the-art 3D tracking (powered by u-track 3D , under submission for peer-review from the Danuser Lab).

Courtesy of Liang Gao Lab, Stony Brook University, Collected with TLS-SPM

User stories

Amira Software is a popular 3D data analysis application, used daily by thousands of researchers and scientists worldwide.

Amira user stories

Scientific publications

Documents and Links

Amira for Life Sciences brochure

Read how Amira Software allows to get more detailed insight in life sciences data sets.

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