Techniques & Applications

• Physical metallurgy, engineered materials and welds
• Failure analysis
• Dental restorative materials and amalgams, including reactions with mercury
• Ion implantation of materials
• Polymer science
• Analysis of thin film multi-layers
• Semiconductors
• Petroleum geology and core sampling
• Mineralogical characterization
• Igneous petrology
• Geochemistry
• Particle characterisation from smoke stack emissions
• Nano-imaging
• Microfossil identification and characterisation 

• Immuno electron microscopy
• Stereology
• Ultramicrotomy applied to biological and physical materials
• SEM preparation using critical point drying
• High resolution rotary shadowing and negative staining of macromolecules, viruses and bacteria
• Development of specific protocols for the preparation of plant and animal tissue
• Live cell imaging
• Nano imaging of cell ultrastructures
• Laser microdissection for PCR, RT-PCR and Proteomics etc. 

Imaris provides a complete set of features for visualization of multi-channel microscopy datasets from static 2D images to 3D time series regardless of their size and format.

• Organise and manage full experiments including images and data analysis in Imaris Arena
• Use premier 3D/4D volume rendering modes: (MIP, Blend, Shadow Projection, Normal Shading)
• Benefit from Imaris’ high performance IMS file format which guarantees smooth navigation even in very large datasets
• Combine volume rendering, object representation, clipping planes and 2D slicers
• Make high quality snapshots ready for presentations and publications in Snapshot Tool
• Easily make animations which include volume rendering, detected objects, annotations and object motion by adding several frames of interest in the Key Frame Animation Tool
• Automated detection of cells and organelles
• Plotting, statistical tests and group comparisons
• Co-localisation 

Imaris for Tracking gives the choice of proven Imaris 3D tracking algorithms: Brownian Motion, Autoregresive Motion (Expert), Connected Components or Lineage to generate the most accurate tracking results for different types of moving objects. Users can automatically correct translational and rotational drift or track within the new freehand coordinate system (Reference Frame) or use the automated option for drift correction.

• Motion - Automatically track objects of interest using one of the provided algorithms
• Handle thousands of objects and time points
• Represent trajectory or displacement using multiple visualization options
• Calculate average and instantaneous speed, acceleration
• Manually create and edit tracks 
• Use the provided lineage algorithm designed for tracking dividing cells and nuclei
• Explore cell fate from one progenitor cell to the final generation
• Automatically create an editable lineage tree
• Mark selected lineage tree branches with coloured labels and analyse your data per lineage
• Calculate Cell Cycle Duration, Generation, Time Since First Division, Time Since Previous Division

Imaris for Cell Biologists provides multiple options to detect and model your biologically relevant structures via step-by-step wizards with a preview of the results at each point in the workflow. 

• Computer-generated representations of a specified region of interest in the data set
• Act as a container from which all the desired statistics can be calculated
• Can be tracked in time (position, shape and intensity changes)
• XYZ coordinates of each objects are calculated, relative distances to other objects can be measured
• Segments multiple biological components simultaneously (e.g. cells based on membrane or cytoplasm labels, nuclei, lysosomes, vesicles)
• Performs image analysis on a per cell basis (e.g. number of vesicles per cell, distance of each vesicle from cell boundary)
• Measures relative distance from vesicles or other organelles to cell membrane or nuclei border
• Precisely segments touching or sparse objects like cells with plasma membrane, nuclear envelope or cell wall staining only
• Inspects the quality of segmentation in all directions using 2D slicers
• Counts objects within the specified region of interest (whole dataset or subset)
• Reports morphological measurements such as volume, bounding box length and sphericity

Automatic neuron tracing is guided within the wizard based interface – starting point and seed points along the filament are detected with just few mouse clicks.

• Dedicated algorithms available for trees without loops or structures which may contain loops.
• Adjust multiple parameters to ensure the best possible detection quality: amend automatically calculated threshold, add/delete start or end points of the filament.
• Segmenting images even with sub-optimal quality (e.g. overall low signal to noise ratio and/or in the presence of high intensity (non-filament) points in the background).
• All dendritic spines along the filament and creates a new class of objects