Amira (software)
Screenshot of Amira Window | |
Developer(s) |
Zuse Institute Berlin FEI Visualization Sciences Group |
---|---|
Initial release | October 1999 |
Stable release | 6.0.1 / July 8, 2015 |
Written in | C++ |
Operating system |
Microsoft Windows XP(SP3)/Vista/7, 32-bit and 64-bit Mac OS X 10.5 (Leopard), 32-bit Mac OS X 10.6 (Leopard), 32-bit Mac OS X 10.7 (Lion), 32-bit Linux x86_64 RHEL 5.5, 64-bit |
Platform | x86 & x86-64 |
Available in | English language |
Type | 3D data visualization and processing |
License | Proprietary |
Website |
www |
Amira (pronounce: Ah-meer-ah) is a software platform for 3D and 4D data visualization, processing, and analysis. It is being actively developed by Visualization Sciences Group, Bordeaux, France and the Zuse Institute Berlin (ZIB), Germany.
Overview
Amira[1] is an extendable software system for scientific visualization, data analysis, and presentation of 3D and 4D data. Amira is being developed and commercially distributed by FEI Visualization Sciences Group, Bordeaux in cooperation with the Zuse Institute Berlin (ZIB). It is used by several thousand researchers and engineers in academia and industry around the world. Amira’s flexible user interface and its modular architecture make it a universal tool for processing and analysis of data from various modalities; e.g. micro-CT,[2] PET,[3] Ultrasound.[4] Its ever expanding functionality has made it a versatile data analysis and visualization solution, applicable to and being used in many fields, such as microscopy in biology[5] and materials science,[6] molecular biology,[7] quantum physics,[8] astrophysics,[9] computational fluid dynamics (CFD),[10] finite element modeling (FEM),[11] non-destructive testing (NDT),[12] and many more. One of the key features, besides data visualization, is Amira’s set of tools for image segmentation[13] and geometry reconstruction.[14] This allows the user to mark (or segment) structures and regions of interest in 3D image volumes using automatic, semi-automatic, and manual tools. The segmentation can then be used for a variety of subsequent tasks, such as volumetric analysis,[4] density analysis,[15] shape analysis,[16] or the generation of 3D computer models for visualization,[17] numerical simulations,[18] or rapid prototyping[19] or 3D printing, to name a few. Other key Amira features are multi-planar and volume visualization, image registration,[20] filament tracing,[21] cell separation and analysis,[16] tetrahedral mesh generation,[22] fiber-tracking from diffusion tensor imaging (DTI) data,[23] skeletonization,[24] spatial graph analysis, and stereoscopic rendering[25] of 3D data over multiple displays including CAVEs (Cave automatic virtual environments).[26] As a commercial product Amira requires the purchase of a license or an academic subscription. A time-limited, but full-featured evaluation version is available for download free of charge.
History
1994–1998 Research Software
Amira’s roots go back to 1994 and the Department for Scientific Visualization, headed by Hans-Christian Hege at the Zuse Institute Berlin (ZIB). The ZIB is a research institute for mathematics and informatics. The Scientific Visualization department’s mission is to help solve computationally and scientifically challenging tasks in medicine, biology, and engineering. For this purpose, it develops algorithms and software for 2D, 3D, and 4D data visualization and visually supported exploration and analysis. At that time, the young visualization group at the ZIB had experience with the extendable, data flow-oriented visualization environments apE,[27] IRIS Explorer,[28] and Advanced Visualization Studio (AVS), but was not satisfied with these products’ interactivity, flexibility, and ease-of-use for non-computer scientists.
Therefore, in a subproject[29] within a medically oriented, multi-disciplinary collaborative research center[30] the development of a new software system was started in early 1994. The initial development was performed by Detlev Stalling, who later became the chief software architect. The software system was called “HyperPlan”, highlighting its initial target application – a planning system for hyperthermia cancer treatment. The system was being developed on Silicon Graphics (SGI) computers, which at the time were the standard workstations used for high-end graphics computing. Software development was based on libraries such as OpenGL, SGI Open Inventor, and the graphical user interface libraries X11, Motif (software), and ViewKit. In 1998, X11/Motif/Viewkit were replaced by the Qt toolkit.
The HyperPlan framework served as the base for more and more projects at the ZIB and was used by a growing number of researchers in collaborating institutions. The projects included applications in neurobiology, confocal microscopy, flow visualization, molecule visualization and analysis and computational astrophysics.
1998–today Commercially Supported Product
The growing number of users of the system started to exceed the capacities that ZIB could spare for software distribution and support, as ZIB’s primary mission was algorithmic research. Therefore, the spin-off company Indeed, – Visual Concepts GmbH was founded by Hans-Christian Hege, Detlev Stalling, and Malte Westerhoff with the vision of making the extensive capabilities of the software available to researchers in industry and academia worldwide and to provide the product support and robustness needed in today’s fast-paced and competitive world.
In Feb 1998 the HyperPlan software was given the new, less application-specific name “Amira”. This name is not an acronym but was chosen for being pronounceable in different languages, starting with an ‘A’, and having an appropriate connotation: the Latin verb “admirare” (to admire), meaning “to look at” and “to wonder at”, describes a typical situation in data visualization.
A major re-design of the software was undertaken by Detlev Stalling and Malte Westerhoff in order to make it a commercially supportable product and to make it available on non-SGI computers as well. In March 1999, the first version of the commercial Amira was shown at the CeBIT tradeshow in Hannover, Germany on SGI IRIX and Hewlett-Packard UniX (HP-UX). Versions for Linux and Microsoft Windows followed within the following twelve months. Later Mac OS X support was added. Indeed, – Visual Concepts selected the Bordeaux, France and San Diego, USA based company TGS, Inc. as the worldwide distributor for Amira and completed five major releases (up to version 3.1) in the subsequent four years.
In 2003 both Indeed, as well as TGS were acquired by Massachusetts-based Mercury Computer Systems, Inc. (NASDAQ:MRCY) and became part of Mercury’s newly formed life sciences business unit, later branded Visage Imaging. In 2009, Mercury Computer Systems, Inc. spun off Visage Imaging again and sold it to Melbourne, Australia based Promedicus Ltd (ASX:PME), a leading provider of radiology information systems and medical IT solutions. During this time, Amira continued to be developed in Berlin, Germany and in close collaboration with the ZIB, still headed by the original creators of Amira. TGS, located in Bordeaux, France was sold by Mercury Computer systems to a French investor and renamed to Visualization Sciences Group (VSG). VSG continued the work on a complementary product named Avizo, based on the same source code but customized for material sciences.
In August 2012, FEI, to that date the largest OEM reseller of Amira, purchased VSG and the Amira business from Promedicus. In August 2013 Visualization Sciences Group (VSG) has been renamed to FEI Visualization Sciences Group. Amira and Avizo are still being marketed as two different products; Amira for life sciences and Avizo for material sciences, but the development efforts are now joined once again. As in the beginning, the Amira roadmap continues to be driven by the interesting and challenging scientific questions that Amira users around the world are trying to answer, often at the leading edge in their fields.
The latest version, Amira 5.4.3, was released in October 2012, with the next release planned for the second quarter of 2013.
Amira Options
Microscopy Option
- Specific readers for microscopy data
- Image deconvolution
- Exploration of 3D imagery obtained from virtually any microscope
- Extraction and editing of filament networks from microscopy images
DICOM Reader
- Import of clinical and preclinical data in DICOM format
Mesh Option
- Generation of 3D finite element (FE) meshes from segmented image data
- Support for many state-of-the-art FE solver formats
- High-quality visualization of simulation mesh-based results, using scalar, vector, and tensor field display modules
Skeletonization Option
- Reconstruction and analysis of neural and vascular networks
- Visualization of skeletonized networks
- Length and diameter quantification of network segments
- Ordering of segments in a tree graph
- Skeletonization of very large image stacks
Molecular Option
- Advanced tools for the visualization of molecule models
- Hardware-accelerated volume rendering
- Powerful molecule editor
- Specific tools for complex molecular visualization
Developer Option
- Creation of new custom components for visualizing or data processing
- Implementation of new file readers or writers
- C++ programming language
- Development wizard for getting started quickly
Neuro Option
- Medical image analysis for DTI and brain perfusion
- Fiber tracking supporting several stream-line based algorithms
- Fiber separation into fiber bundles based on user defined source and destination regions
- Computation of tensor fields, diffusion weighted maps
- Eigenvalue decomposition of tensor fields
- Computation of mean transit time, cerebral blood flow, and cerebral blood volume
VR Option
- Visualization of data on large tiled displays or in immersive Virtual Reality (VR) environments
- Support of 3D navigation devices
- Fast multi-threaded and distributed rendering
Very Large Data Option
- Support for visualization of image data exceeding the available main memory, using efficient out-of-core data management
- Extensions of many standard modules, such as orthogonal and oblique slicing, volume rendering, and isosurface rendering, to work on out-of-core data
Editors
- CameraPath Editor: create a camera path using key-frames for animations and movies
- Color Dialog: define a color value using a graphical interface
- 2 Colormap Editors: modify the RGBA values of a discrete colormap
- Curve Editor: create and edit curves
- Demo Manager: manage and control demos using a graphical interface
- Digital Image Filters: apply standard image processing filters
- Filament Editor: skeletonize image data and modify spatial graphs
- Grid Editor: edit and simplify tetrahedral grids
- Image Crop Editor: crop 3D images, change bounding box, and voxel size
- Landmark Editor: add, move, or delete markers in a landmark set
- LineSet Editor: select, create, modify, and delete polylines
- Multi-planar Viewer: view up to two data sets simultaneously in a 3+1 MPR viewer
- Parameter Editor: add, change, or delete attributes of a data object
- Plot Tool: display 2D plots
- Segmentation Editor: 3D image segmentation using interactive and semi-automatic tools
- Surface Simplification Editor: reduce the number of triangles of a triangulated surface
- Surface Editor: modify triangles, remove intersections, assign boundary ids in triangulated surfaces
- Transform Editor: translate, rotate, or scale any 3D data object
Application Areas
- Anatomy[31][32]
- Biochemistry[33]
- Biophysics[33]
- Cellular microbiology[34][35]
- Computational fluid dynamics[36]
- Cryo-electron tomography[34]
- Diffusion MRI/Fiber Tracking
- Embryology[31]
- Endocrinology[37]
- Finite Element Modelling[38]
- Histology[31][33][39]
- Medical imaging research
- Microscopy in life and material sciences
- Molecular biology[40]
- Neuroscience[39][41]
- Nondestructive testing
- Orthopedics[38][42][43]
- Otolaryngology[44]
- Preclinical imaging[40]
- Urology[45]
Processing and Data Analysis
- Surface and grid generation
- 3D image segmentation
- Image registration and slice alignment
- Skeletonization and deconvolution
- Multitude of quantification tools
- Arithmetic operations
- MATLAB integration
- 2D and 3D image filtering
- Surface generation
- Finite element model (FEM) grid generation
- Interactive and automatic segmentation
- Interactive and automatic slice alignment
- Image registration and morphing
- Tensor computation
- Skeletonization and tracing of neural and vascular networks
- Deconvolution and z-drop correction
- Powerful scripting interface
- Dedicated editors for segmentation, tracing, and fusion
Visualization
- Orthogonal and oblique slicing
- Volume rendering
- Surface rendering
- Isolines and isosurfaces
- Multi-channel imaging and fusion
- Vector and tensor visualization
- Support of structured / unstructured grids
- Molecular simulation and visualization
- Structured workflow visualization
- Active and passive stereo support
- Tiled screen support
- Virtual reality navigation and tools
Presentation
- Easy-to-use interactive 3D navigation
- Tools for designing animated demos
- Automation of complex animations and demonstrations
- Embedded tools for movie generation
- Active and passive 3D stereo vision
- 2D and 3D annotation
- Support for stereoscopic and auto-stereoscopic displays
- Virtual reality navigation tools
- Single and tiled screen display
- Single or multi-pipe rendering
- Support for "trackd" input devices
- Geometry data
- Scalar fields and all types of multidimensional images
- Vector and flow data
- Tensor fields
- Molecular models
- Simulation data on finite element models
Supported File Formats
Format Name | Access Type | Description |
---|---|---|
Amira Script | read/write | Amira Tcl script |
Amira Script Object | read/write | Amira custom module written in Tcl |
AmiraMesh Format | read/write | Amira's native general purpose format |
AmiraMesh as LargeDiskData | read/write | access image data blockwise |
Analyze 7.5 | read/write | 3D image data with separate header file |
AnalyzeAVW | read/write | contains 2D and 3D medical image data |
BMP Image Format | read/write | uncompressed Windows bitmap format |
AutoCAD DXF | read/write | Drawing Interchange Format for AutoCAD 3D models |
Encapsulated PostScript | write | for 2D raster images only |
HTML | read | Hypertext document format |
Hoc | read/write | Hoc file reader of morphometric models for NEURON environment |
HxSurface | read/write | Amira's native format for triangular surfaces |
Icol | read/write | ASCII format for colormaps with alpha channel |
Interfile | read | Interfile file reader |
JPEG Image Format | read/write | 2D image format with lossy compression |
MATLAB Binary Format (.mat) | read/write | MATLAB matrices |
MATLAB M-files Format (.m) | read/write | MATLAB script |
Nifti | read/write | Nifti file reader |
Open Inventor | read/write | standard file format for 3D models |
PNG Image Format | read/write | portable network graphics format for 2D images |
PNM Image Format | read/write | simple uncompressed 2D image format |
PSI format | read/write | ASCII format for 3D points and associated data values |
PLY Format | read/write | Stanford triangle format for points and surfaces |
Raw Data | read/write | binary data as a 3D uniform field |
Raw Data as LargeDiskData | read/write | access image data blockwise |
SGI-RGB Image Format | read/write | 2D image format with run-length encoding |
STL | read/write | simple format for triangular surfaces, no connectivity |
SWC | read/write | interchange-file reader of morphometric models for neuroscience |
Stacked-Slices | read | info file grouping together 2D images |
TIFF Image Format | read/write | standard format for 2D and 3D image data |
Tecplot | read | Tecplot ASCII and Binary file reader |
VRML | read/write | virtual reality markup language for 3D models |
Vevo Mode Raw Images | read | 2D and 3D ultrasound images from VisualSonics' Vevo 770 |
Wavefront Technologies 3D Geometry (.obj) | write | 3D geometries such as surfaces |
AMBER | read | Assisted Model Building with Energy Refinement format |
AMF | read/write | Amira Molecule Format |
DX | read | APBS DX electrostatic field file |
GROMACS | read/write | Groningen Machine for Chemical Simulations format |
MAP | read | Autogrid interaction field file |
MDL | read/write | MDL file format saving chemical structures |
PDB | read/write | protein data base file format |
PHI | read | Congen PHI Electrostatic field file (r) |
PSF/DCD (CHARMM) | read | file format used by CHARMM |
Tripos | read/write | file format used to save Tripos Sybyl mol2 molecules |
UniChem | read/write | file format used by the UniChem molecular software |
ZIB Molecular File Format | read/write | structured molecular file format |
Amira Virtual Reality Option Config File | read | Amira Virtual Reality Option Config File (.cfg) |
LDA | read | VolumeViz native file format |
LargeDiskData | read/write | access image data blockwise |
Stacked-Slices as LargeDiskData | read | access image data blockwise |
AVS Field | read/write | stores data defined on regular grid |
AVS UCD Format | read/write | stores unstructured cell data |
Abaqus format | write | describes FEM grids and density data |
FIDAP NEUTRAL | read | stores FEM meshes and solution data |
Fluent / UNS | read/write | contains FEM meshes, boundary ids, solution data |
HyperMesh | read/write | used by Altair HyperWorks FEM software |
I-DEAS universal format | read/write | describes FEM grids and simulation data |
Plot 3D Single Structured | read/write | stores curvilinear grids and associated data |
Bio-Rad Confocal Format | read | simple uncompressed format for 3D image stacks |
FEIStackedScalarField3 | read | scalar fields consisting of parallel slices (MRC format) |
FEIUniformScalarField3 | read | scalar fields defined on a uniform lattice (MRC format) |
Leica 3D TIFF | read | contains 3D image data with voxel sizes |
Leica Binary Format (.lei) | read | 3D image stacks, time series, and meta information |
Leica Image Format (.lif) | read | 3D image stacks, time series, and meta information |
Leica Slice Series (.info) | read | contains list of 2D TIFF files and meta information |
MRC | read/write | MRC file format for electron microscopy |
Metamorph STK Format | read | special TIFF variant for 3D image stacks |
Olympus (.oib/.oif) | read | file formats used by the Olympus FluoView 1000F |
Zeiss LSM | read | 3D raster image format |
ACR-NEMA | read | predecessor of the DICOM format for medical images |
DICOM export | write | medical image export |
DICOM import | read | standard file format for medical images |
Release history
Version | Release Date | Supported Platforms |
---|---|---|
public BETA |
Dec 1998 | SGI Irix 6.x |
public BETA |
Mar 1999 | SGI Irix 6.x HP-UX 10.20 32-bit Linux: Red Hat 5.2, SuSE 6.0 (Linux: software rendering only) |
2.0.0 | Oct 1999 | SGI Irix 6.5.x HP-UX 10.20 32-bit Linux: Red Hat 6.0, SuSE 6.1 |
2.1.0 | Mar 2000 | Microsoft Windows 9x/NT4 32-bit Linux: Red Hat 6.x, SuSE 6.3 SGI Irix 6.5.x HP-UX 10.20 Sun Solaris 7 (SunOS 5.7) |
2.1.1 | May 2000 | Microsoft Windows 9x/NT4 32-bit Linux: Red Hat 6.x, SuSE 6.3 SGI Irix 6.5.x HP-UX 10.20 Sun Solaris 7 (SunOS 5.7) |
2.2.0 | Sep 2000 | Microsoft Windows 9x/NT4/2000 32-bit Linux: Red Hat 6.2, SuSE 6.3 SGI Irix 6.5.x HP-UX 10.20 Sun Solaris 7 (SunOS 5.7) |
2.3.0 | Aug 2001 | Microsoft Windows 9x/ME/NT4/2000, 32-bit Linux: Red Hat 7.x, SuSE 7.x SGI Irix 6.5.x HP-UX 11.0 Sun Solaris 7 (SunOS 5.7) |
3.0.0 | Jul 2002 | Microsoft Windows 98/ME/NT4/2000/XP, 32-bit Linux: Red Hat 8.0 SGI Irix 6.5.x Sun Solaris 8 HP-UX 11.0 |
3.1.0 | Dec 2003 | Microsoft Windows 98/ME/NT4/2000/XP, 32-bit Linux IA64 (Red Hat AW 2.1), 64-bit Linux Red Hat 8.0 (<=glibc-2.3.2), 32-bit Linux SUSE 9.0 (x86-64), 64-bit Sun Solaris 8/9, 32/64-bit SGI Irix 6.5.x, 32/64-bit HP-UX 11.0, 32/64-bit |
3.1.1 | Jun 2004 | Microsoft Windows 98/ME/NT4/2000/XP, 32-bit Linux IA64 (Red Hat AW 2.1), 64-bit Linux Red Hat 8.0 (<=glibc-2.3.2), 32-bit Linux SUSE 9.0 (x86-64), 64-bit Sun Solaris 8/9, 32/64-bit SGI Irix 6.5.x, 32/64-bit HP-UX 11.0, 32/64-bit |
4.0.0 | Dec 2005 | Microsoft Windows XP 2003 (x86-64), 64-bit Microsoft Windows 2000/XP, 32-bit Linux IA64 (RHEL 3.0, Itanium 2), 64-bit Linux x86-64 (RHEL 3.0), 64-bit Linux x86 (RHEL 3.0), 32-bit Mac OS X 10.4(Tiger), 32-bit Sun Solaris 8, 32/64-bit SGI Irix 6.5.x, 32/64-bit HP-UX 11.0, 32/64-bit |
4.1.0 | May 2006 | Microsoft Windows XP 2003 (x86-64), 64-bit Microsoft Windows 2000/XP, 32-bit Linux IA64 (RHEL 3.0, Itanium 2), 64-bit Linux x86-64 (RHEL 3.0), 64-bit Linux x86 (RHEL 3.0), 32-bit Sun Solaris 8, 32/64-bit SGI Irix 6.5.x, 32/64-bit HP-UX 11.0, 32/64-bit |
4.1.1 | Oct 2006 | Microsoft Windows XP 2003 (x86-64), 64-bit Microsoft Windows 2000/XP, 32-bit Linux IA64 (RHEL 3.0, Itanium 2), 64-bit Linux x86-64 (RHEL 3.0), 64-bit Linux x86 (RHEL 3.0), 32-bit Mac OS X 10.4 (Tiger), 32-bit Sun Solaris 8, 32/64-bit SGI Irix 6.5.x, 32/64-bit HP-UX 11.0, 32/64-bit |
4.1.2 | Feb 2007 | Microsoft Windows XP 2003 (x86-64), 64-bit Microsoft Windows 2000/XP, 32-bit Linux IA64 (RHEL 3.0, Itanium 2), 64-bit Linux x86-64 (RHEL 3.0), 64-bit Linux x86 (RHEL 3.0), 32-bit Mac OS X 10.4 (Tiger), 32-bit Sun Solaris 8, 32/64-bit SGI Irix 6.5.x, 32/64-bit HP-UX 11.0, 32/64-bit |
5.0.0 | May 2008 | Microsoft Windows 2000/XP/Vista (x86-64), 64-bit Microsoft Windows 2000/XP/Vista, 32-bit |
5.0.1 | Jun 2008 | Microsoft Windows 2000/XP/Vista (x86-64), 64-bit Microsoft Windows 2000/XP/Vista, 32-bit |
5.2.0 | Nov 2008 | Microsoft Windows 2000/XP/Vista (x86-64), 64-bit Microsoft Windows 2000/XP/Vista, 32-bit Mac OS X 10.5 (Leopard), 32-bit Linux x86-64 (RHEL 5.2), 64-bit |
5.2.1 | Mar 2009 | Microsoft Windows 2000/XP/Vista (x86-64), 64-bit Microsoft Windows 2000/XP/Vista, 32-bit Mac OS X 10.5 (Leopard), 32-bit Linux x86-64 (RHEL 5.2), 64-bit |
5.2.2 | Jul 2009 | Microsoft Windows 2000/XP/Vista (x86-64), 64-bit Microsoft Windows 2000/XP/Vista, 32-bit Mac OS X 10.5 (Leopard), 32-bit Linux x86-64 (RHEL 5.2), 64-bit |
5.3.0 | Jun 2010 | Microsoft Windows 2000/XP/Vista (x86-64), 64-bit Microsoft Windows 2000/XP/Vista, 32-bit Mac OS X 10.5 (Leopard), 32-bit Mac OS X 10.6 (Snow Leopard), 32-bit Linux x86-64 (RHEL 5.5), 64-bit |
5.3.1 | Jul 2010 | Microsoft Windows 2000/XP/Vista (x86-64), 64-bit Microsoft Windows 2000/XP/Vista, 32-bit Mac OS X 10.5 (Leopard), 32-bit Mac OS X 10.6 (Snow Leopard), 32-bit Linux x86-64 (RHEL 5.5), 64-bit |
5.3.2 | Oct 2010 | Microsoft Windows 2000/XP/Vista (x86-64), 64-bit Microsoft Windows 2000/XP/Vista, 32-bit Mac OS X 10.5 (Leopard), 32-bit Mac OS X 10.6 (Snow Leopard), 32-bit Linux x86-64 (RHEL 5.5), 64-bit |
5.3.3 | Dec 2010 | Microsoft Windows 2000/XP/Vista (x86-64), 64-bit Microsoft Windows 2000/XP/Vista, 32-bit Mac OS X 10.5 (Leopard), 32-bit Mac OS X 10.6 (Snow Leopard), 32-bit Linux x86-64 (RHEL 5.5), 64-bit |
5.4.0 | Oct 2011 | Microsoft Windows XP/Vista/7 (x86-64), 64-bit Microsoft Windows XP/Vista/7, 32-bit Mac OS X 10.5 (Leopard), 32-bit Mac OS X 10.6 (Snow Leopard), 32-bit Mac OS X 10.7 (Lion), 32-bit Linux x86-64 (RHEL 5.5), 64-bit |
5.4.1 | Dec 2011 | Microsoft Windows XP/Vista/7 (x86-64), 64-bit Microsoft Windows XP/Vista/7, 32-bit Mac OS X 10.5 (Leopard), 32-bit Mac OS X 10.6 (Snow Leopard), 32-bit Mac OS X 10.7 (Lion), 32-bit Linux x86-64 (RHEL 5.5), 64-bit |
5.4.2 | Mar 2012 | Microsoft Windows XP/Vista/7 (x86-64), 64-bit Microsoft Windows XP/Vista/7, 32-bit Mac OS X 10.5 (Leopard), 32-bit Mac OS X 10.6 (Snow Leopard), 32-bit Mac OS X 10.7 (Lion), 32-bit Linux x86-64 (RHEL 5.5), 64-bit |
5.4.3 | Oct 2012 | Microsoft Windows XP/Vista/7 (x86-64), 64-bit Microsoft Windows XP/Vista/7, 32-bit Mac OS X 10.5 (Leopard), 32-bit Mac OS X 10.6 (Snow Leopard), 32-bit Mac OS X 10.7 (Lion), 32-bit Linux x86-64 (RHEL 5.5), 64-bit |
5.4.4 | Mar 2013 | Microsoft Windows XP/Vista/7 (x86-64), 64-bit Microsoft Windows XP/Vista/7, 32-bit Mac OS X 10.5 (Leopard), 32-bit Mac OS X 10.6 (Snow Leopard), 32-bit Mac OS X 10.7 (Lion), 32-bit Linux x86-64 (RHEL 5.5), 64-bit |
5.4.5 | Mar 2013 | Microsoft Windows XP/Vista/7 (x86-64), 64-bit Microsoft Windows XP/Vista/7, 32-bit Mac OS X 10.5 (Leopard), 32-bit Mac OS X 10.6 (Snow Leopard), 32-bit Mac OS X 10.7 (Lion), 32-bit Linux x86-64 (RHEL 5.5), 64-bit |
5.5.0 | Oct 2013 | Microsoft Windows XP/Vista/7 (x86-64), 64-bit Microsoft Windows XP/Vista/7, 32-bit Mac OS X 10.7 (Lion), 64-bit Mac OS X 10.8 (Mountain Lion), 64-bit Linux x86-64 (RHEL 5.5), 64-bit |
5.6.0 | Apr 2014 | Microsoft Windows XP/Vista/7/8 (x86-64), 64-bit Microsoft Windows XP/Vista/7/8, 32-bit Mac OS X 10.7/10.8 (Lion), 64-bit Mac OS X 10.8 (Mountain Lion), 64-bit Linux x86-64 (RHEL 5.5), 64-bit |
6.0 | Jan 2015 | Microsoft Windows 7/8 (x86-64), 64-bit Microsoft Windows 7/8, 32-bit Mac OS X 10.7 (Lion), 64-bit Mac OS X 10.8 (Mountain Lion), 64-bit Mac OS X 10.9 (Mavericks), 64-bit Linux x86-64 (RHEL 6), 64-bit |
References
- ↑ Stalling, D.; Westerhoff, M.; Hege, H.-C. (2005). C.D. Hansen and C.R. Johnson, ed. "Amira: A Highly Interactive System for Visual Data Analysis". The Visualization Handbook (Elsevier): 749–767. CiteSeerX: 10
.1 ..1 .129 .6785 - ↑ Adam, R.; Smith, A.R.; Sieren, J.C.; Eggleston, T.; McLennan, G. (2010). "Characterization Of The Airways And Lungs For The FABP/CFTR-Knockout Mouse Using Micro-Computed Tomography And Large Image Microscope Array" (PDF). American Journal of Respiratory and Critical Care Medicine (Am Thoracic Soc) 181: A6264. doi:10.1164/ajrccm-conference.2010.181.1_meetingabstracts.a6264.
- ↑ Awasthi, V.; Holter, J.; Thorp, K.; Anderson, S.; Epstein, R. (2010). "F-18-fluorothymidine-PET evaluation of bone marrow transplant in a rat model". Nuclear Medicine Communications 31 (2): 152–158. doi:10.1097/mnm.0b013e3283339f92.
- 1 2 Ayers, G.D.; McKinley, E.T.; Zhao, P.; Fritz, J.M.; Metry, R.E.; Deal, B.C.; Adlerz, K.M.; Coffey, R.J.; Manning, H.C. (2010). "Volume of Preclinical Xenograft Tumors Is More Accurately Assessed by Ultrasound Imaging Than Manual Caliper Measurements". Journal of Ultrasound in Medicine (Am inst Ultrasound Med) 29 (6): 891.
- ↑ Dlasková, A.; Spacek, T.; Santorová, J.; Plecitá-Hlavatá, L.; Berková, Z.; Saudek, F.; Lessard, M.; Bewersdorf, J.; Jezek, P. (2010). "4Pi microscopy reveals an impaired three-dimensional mitochondrial network of pancreatic islet beta-cells, an experimental model of type-2 diabetes.". Biochimica et Biophysica Acta (BBA) - Bioenergetics (Elsevier) 1797: 1327–1341. doi:10.1016/j.bbabio.2010.02.003.
- ↑ Clark, N.D.L.; Daly., C. (2010). "Using confocal laser scanning microscopy to image trichome inclusions in amber" (PDF). Journal of Paleontological Techniques 8.
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