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Amira
Developer(s)Zuse Institute Berlin
Thermo Fisher Scientific
Initial releaseOctober 1999; 24 years ago (1999-10)
Stable release
2020.3 / February 2021; 3 years ago (2021-02)
Operating systemWindows XP SP3, Windows Vista, Windows 7
OS X 10.5, OS X 10.6, OS X 10.7
RHEL 5.5
PlatformIA-32, x64
Available inEnglish
Type3D data visualization and processing
LicenseTrialware
Websitethermofisher.com/amira-avizo

Amira (pronounce: Ah-meer-ah) is a software platform for visualization, processing, and analysis of 3D and 4D data. It is being actively developed by Thermo Fisher Scientific in collaboration with the Zuse Institute Berlin (ZIB), and commercially distributed by Thermo Fisher Scientific — together with its sister software Avizo.

Overview

Amira[1] is an extendable software system for scientific visualization, data analysis, and presentation of 3D and 4D data. It is used by thousands of researchers and engineers in academia and industry around the world. Its flexible user interface and 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 and immersive virtual reality environments, including CAVEs.[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

1993–1998: Research software

Amira’s roots go back to 1993 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, engineering and materials science. 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, the development of a new software system was started in a research project[29] within a medically oriented, multi-disciplinary collaborative research center.[30] Based on experiences that Tobias Höllerer had gained in late 1993 with the new graphics library IRIS Inventor,[31] it was decided to utilize that library. The development of the medical planning system was performed by Detlev Stalling, who later became the chief software architect of Amira. The new software 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. The software was based on libraries such as OpenGL (originally IRIS GL), Open Inventor (originally IRIS 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 medical image computing, medical visualization, neurobiology, confocal microscopy, flow visualization, molecular analytics 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.

In Feb 1998 the HyperPlan software was given the new, application-neutral name “Amira”. This name is not an acronym, but was chosen for being pronounceable in different languages and providing a suitable connotation, namely “to look at” or “to wonder at”, from the Latin verb “admirare” (to admire), which reflects a basic situation in data visualization.[citation needed]

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 exhibited at the CeBIT tradeshow in Hannover, Germany on SGI IRIX and Hewlett-Packard UniX (HP-UX) booths. Versions for Linux and Microsoft Windows followed within the following twelve months. Later Mac OS X support was added. Indeed – Visual Concepts GmbH selected the Bordeaux, France and San Diego, United States 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 – Visual Concepts GmbH, as well as TGS, Inc. 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. This brought the two software sisters Amira and Avizo back into one hand. In August 2013, Visualization Sciences Group (VSG) became a business unit of FEI. In 2016 FEI has been bought by Thermo Fisher Scientific and became part of its Materials & Structural Analysis division in early 2017.

Amira and Avizo are still being marketed as two different products; Amira for life sciences and Avizo for materials science, but the development efforts are now joined once again. In the meantime, the number of scientific articles using the Amira / Avizo software, is in the order of 10 thousands.[citation needed]

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

Application areas

References

  1. ^ 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: 749–767. CiteSeerX 10.1.1.129.6785. doi:10.1016/B978-012387582-2/50040-X. ISBN 9780123875822.
  2. ^ 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. 181: A6264. doi:10.1164/ajrccm-conference.2010.181.1_meetingabstracts.a6264.
  3. ^ 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. PMID 19966596. S2CID 44923538.
  4. ^ a b 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. 29 (6): 891–901. doi:10.7863/jum.2010.29.6.891. PMC 2925269. PMID 20498463.
  5. ^ 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. 1797 (6–7): 1327–1341. doi:10.1016/j.bbabio.2010.02.003. PMID 20144584.
  6. ^ Clark, N.D.L.; Daly., C. (2010). "Using confocal laser scanning microscopy to image trichome inclusions in amber" (PDF). Journal of Paleontological Techniques. 8.
  7. ^ Amstalden van Hove, E.R.; Blackwell, T.R.; Klinkert, I.; Eijkel, G.B.; Heeren, R.; Glunde, K. (2010). "Multimodal Mass Spectrometric Imaging of Small Molecules Reveals Distinct Spatio-Molecular Signatures in Differentially Metastatic Breast Tumor Models". Cancer Research. 70 (22): 9012–9021. doi:10.1158/0008-5472.can-10-0360. PMC 5555163. PMID 21045154.
  8. ^ Sherman, D.M. (2010). "Metal complexation and ion association in hydrothermal fluids: insights from quantum chemistry and molecular dynamics". Frontiers in Geofluids. Vol. 10. pp. 41–57. doi:10.1002/9781444394900.ch4. ISBN 9781444394900. Archived from the original on 2013-01-06.
  9. ^ O'Neill, S.M.; Jones, T.W. (2010). "Three-Dimensional Simulations of Bi-Directed Magnetohydrodynamic Jets Interacting with Cluster Environments". The Astrophysical Journal. 710 (1): 180–196. arXiv:1001.1747. Bibcode:2010ApJ...710..180O. doi:10.1088/0004-637x/710/1/180. S2CID 118617883.
  10. ^ Baharoglu, M.I.; Schirmer, C.M.; Hoit, D.A.; Gao, B.L.; Malek, A.M. (2010). "Aneurysm Inflow-Angle as a Discriminant for Rupture in Sidewall Cerebral Aneurysms". Morphometric and Computational Fluid Dynamic Analysis. Archived from the original on 2010-06-22. Retrieved 2012-05-17.
  11. ^ Bardyn, T.; Gédet, P.; Hallermann, W.; Büchler., P. (2010). "Prediction of dental implant torque with a fast and automatic finite element analysis: a pilot study". Oral Surgery, Oral Medicine, Oral Pathology, Oral Radiology, and Endodontology. 109 (4): 594–603. doi:10.1016/j.tripleo.2009.11.010. PMID 20163974.
  12. ^ Shearing, P.R.; Gelb, J.; Yi, J.; Lee, W.K.; Drakopolous, M.; Brandon, N.P. (2010). "Analysis of Triple Phase Contact in Ni-YSZ Microstructures Using Non-destructive X-ray Tomography with Synchrotron Radiation". Electrochemistry Communications. 12 (8): 1021–1024. doi:10.1016/j.elecom.2010.05.014.
  13. ^ Jährling, N.; Becker, K.; Schönbauer, C.; Schnorrer, F.; Dodt, H.U. (2010). "Three-dimensional reconstruction and segmentation of intact Drosophila by ultramicroscopy". Frontiers in Systems Neuroscience. 4: 1. doi:10.3389/neuro.06.001.2010. PMC 2831709. PMID 20204156.
  14. ^ Zheng, G. (2010). "Statistical shape model-based reconstruction of a scaled, patient-specific surface model of the pelvis from a single standard AP x-ray radiograph". Medical Physics. 37 (4): 1424–1439. Bibcode:2010MedPh..37.1424Z. doi:10.1118/1.3327453. PMID 20443464. Archived from the original on 2012-07-11. Retrieved 2019-05-15.
  15. ^ Rodriguez-Soto, A.E.; Fritscher, K.D.; Schuler, B.; Issever, A.S.; Roth, T.; Kamelger, F.; Kammerlander, C.; Blauth, M.; Schubert, R.; Link, T.M. (2010). "Texture Analysis, Bone Mineral Density, and Cortical Thickness of the Proximal Femur: Fracture Risk Prediction". Journal of Computer Assisted Tomography. 34 (6): 949–957. doi:10.1097/rct.0b013e3181ec05e4. PMID 21084915. S2CID 21196403.
  16. ^ a b Leischner, U.; Schierloh, A.; Zieglgänsberger, W.; Dodt, H.U. (2010). "Formalin-Induced Fluorescence Reveals Cell Shape and Morphology in Biological Tissue Samples". PLOS ONE. 5 (4): e10391. Bibcode:2010PLoSO...510391L. doi:10.1371/journal.pone.0010391. PMC 2861007. PMID 20436930.
  17. ^ Felts, R.L.; Narayan, K.; Estes, J.D.; Shi, D.; Trubey, C.M.; Fu, J.; Hartnell, L.M.; Ruthel, G.T.; Schneider, D.K.; Nagashima, K. (2010). "3D visualization of HIV transfer at the virological synapse between dendritic cells and T cells". Proceedings of the National Academy of Sciences of the United States of America. 107 (30): 13336–13341. Bibcode:2010PNAS..10713336F. doi:10.1073/pnas.1003040107. PMC 2922156. PMID 20624966.
  18. ^ Taylor, D.J.; Doorly, D.J.; Schroter, R.C. (2010). "Inflow boundary profile prescription for numerical simulation of nasal airflow". Journal of the Royal Society Interface. 7 (44): 515–527. doi:10.1098/rsif.2009.0306. PMC 2842801. PMID 19740920.
  19. ^ Lucas, B.C.; Bogovic, J.A.; Carass, A.; Bazin, P.L.; Prince, J.L.; Pham, D.L.; Landman, B.A. (2010). "The Java Image Science Toolkit (JIST) for Rapid Prototyping and Publishing of Neuroimaging Software". Neuroinformatics. 8 (1): 5–17. doi:10.1007/s12021-009-9061-2. PMC 2860951. PMID 20077162.
  20. ^ Dasgupta, S.; Feleppa, E.; Ramachandran, S.; Ketterling, J.; Kalisz, A.; Haker, S.; Tempany, C.; Porter, C.; Lacrampe, M.; Isacson, C. (2007). "8A-4 Spatial Co-Registration of Magnetic Resonance and Ultrasound Images of the Prostate as a Basis for Multi-Modality Tissue-Type Imaging". 2007 IEEE Ultrasonics Symposium Proceedings. pp. 641–643. doi:10.1109/ULTSYM.2007.166. ISBN 978-1-4244-1383-6. S2CID 23656040.
  21. ^ Oberlaender, M.; Bruno, R.M.; Sakmann, B.; Broser, P.J. (2007). "Transmitted light brightfield mosaic microscopy for three-dimensional tracing of single neuron morphology". Journal of Biomedical Optics. 12 (6): 064029. Bibcode:2007JBO....12f4029O. doi:10.1117/1.2815693. PMID 18163845.
  22. ^ Lamecker, H.; Mansi, T.; Relan, J.; Billet, F.; Sermesant, M.; Ayache, N.; Delingette., H. (2009). "Adaptive Tetrahedral Meshing for Personalized Cardiac Simulations". CiteSeerX 10.1.1.698.4292. {{cite journal}}: Cite journal requires |journal= (help)
  23. ^ Boretius, S.; Michaelis, T.; Tammer, R.; Ashery-Padan, R.; Frahm, J.; Stoykova, A. (2009). "In vivo MRI of altered brain anatomy and fiber connectivity in adult pax6 deficient mice". Cerebral Cortex. 19 (12): 2838–2847. doi:10.1093/cercor/bhp057. PMID 19329571.
  24. ^ Kohjiya, S.; Katoh, A.; Suda, T.; Shimanuki, J.; Ikeda, Y. (2006). "Visualisation of carbon black networks in rubbery matrix by skeletonisation of 3D-TEM image". Polymer. 47 (10): 3298–3301. doi:10.1016/j.polymer.2006.03.008.
  25. ^ Clements, R.J.; Mintz, E.M.; Blank, J.L. (2009). "High resolution stereoscopic volume visualization of the mouse arginine vasopressin system". Journal of Neuroscience Methods. 187 (1): 41–45. doi:10.1016/j.jneumeth.2009.12.011. PMID 20036282. S2CID 25746441.
  26. ^ Ohno, N.; Kageyama., A. (2009). "Region-of-interest visualization by CAVE VR system with automatic control of level-of-detail". Computer Physics Communications. 181 (4): 720–725. Bibcode:2010CoPhC.181..720O. doi:10.1016/j.cpc.2009.12.002.
  27. ^ Dyer, D.S. (1990). "A dataflow toolkit for visualization". IEEE Computer Graphics and Applications. 10 (4): 60–69. doi:10.1109/38.56300. S2CID 14426676.
  28. ^ Foulser, D. (1995). "IRIS Explorer: A framework for investigation". ACM SIGGRAPH Computer Graphics. 29 (2): 13–16. doi:10.1145/204362.204365. S2CID 16324076.
  29. ^ "DFG Project: Algorithmen zur Planung und Kontrolle von Hyperthermiebehandlungen". DFG Deutsche Forschungsgemeinschaft. Retrieved 28 January 2015.
  30. ^ "DFG Project SFB 273: Hyperthermia: Methodics and Clinics". DFG Deutsche Forschungsgemeinschaft. Retrieved 28 January 2015.
  31. ^ Strauss, P.S. (1993). "IRIS Inventor, a 3D graphics toolkit". ACM SIGPLAN Notices. 28 (10): 192–200. doi:10.1145/167962.165889.
  32. ^ a b c de Boer, B.A.; Soufan, A.T.; Hagoort, J.; Mohun, T.J.; van den Hoff, M.J.B; Hasman, A.; Voorbraak, F.P.J.M.; Moorman, A.F.M.; Ruijter, J.M. (2011). "The interactive presentation of 3D information obtained from reconstructed datasets and 3D placement of single histological sections with the 3D portable document format". Development. 138 (1): 159–167. doi:10.1242/dev.051086. PMC 2998169. PMID 21138978.
  33. ^ Specht, M.; Lebrun, R.; Zollikofer, C.P.E. (2007). "Visualizing shape transformation between chimpanzee and human braincases" (PDF). The Visual Computer. 23 (9): 743–751. CiteSeerX 10.1.1.108.7163. doi:10.1007/s00371-007-0156-1. S2CID 17472003.
  34. ^ a b c Gaemers, I.C.; Stallen, J.M.; Kunne, C.; Wallner, C.; van Werven, J.; Nederveen, A.; Lamers, W.H. (2011). "Lipotoxicity and steatohepatitis in an overfed mouse model for non-alcoholic fatty liver disease" (PDF). Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease. 1812 (4): 447–458. doi:10.1016/j.bbadis.2011.01.003. PMID 21216282.
  35. ^ a b Kudryashev, M; Cyrklaff, M.; Alex, B.; Lemgruber, L.; Baumeister, W.; Wallich, R.; Frischknecht, F. (2011). "Evidence of direct cell-cell fusion in Borrelia by cryogenic electron tomography". Cellular Microbiology. 13 (5): 731–741. doi:10.1111/j.1462-5822.2011.01571.x. PMID 21276171. S2CID 34114766.
  36. ^ Meisslitzer-Ruppitsch, C.; Röhrl, C.; Ranftler, C.; Neumüller, J.; Vetterlein, M.; Ellinger, A.; Pavelka, M. (2011). "The ceramide-enriched trans-Golgi compartments reorganize together with other parts of the Golgi apparatus in response to ATP-depletion". Histochemistry and Cell Biology. 135 (2): 159–171. doi:10.1007/s00418-010-0773-z. PMID 21225431. S2CID 30748663.
  37. ^ Bevan, R.L.T.; Sazonov, I.; Saksono, P.H.; Nithiarasu, P.; van Loon, R.; Luckraz, H.; Ashral, S. (2011). "Patient-specific blood flow simulation through an aneurysmal thoracic aorta with a folded proximal neck". Numerical Methods in Biomedical Engineering. 27 (8): 1167–1184. doi:10.1002/cnm.1425. S2CID 119410804.
  38. ^ Jiang, Y.; Johnson, G.A. (2010). "Microscopic Diffusion Tensor Imaging of the Mouse Brain". NeuroImage. 50 (2): 465–471. doi:10.1016/j.neuroimage.2009.12.057. PMC 2826147. PMID 20034583.
  39. ^ Bujotzek, A.; Shan, M.; Haag, R.; Weber, M. (2011). "Towards a rational spacer design for bivalent inhibition of estrogen receptor". Journal of Computer-Aided Molecular Design. 25 (3): 253–262. Bibcode:2011JCAMD..25..253B. doi:10.1007/s10822-011-9417-1. PMID 21331802. S2CID 29015240.
  40. ^ a b Cai, W.; Lee, E.Y.; Vij, A.; Mahmood, S.A.; Yoshida, H. (2011). "MDCT for Computerized Volumetry of Pneumothoraces in Pediatric Patients". Academic Radiology. 18 (3): 315–23. doi:10.1016/j.acra.2010.11.008. PMC 3072076. PMID 21216160.
  41. ^ a b Irving, S.; Moore, D.R.; Liberman, M.C.; Sumner, C.J. (2011). "Olivocochlear Efferent Control in Sound Localization and Experience-Dependent Learning". Journal of Neuroscience. 31 (7): 2493–2501. doi:10.1523/jneurosci.2679-10.2011. PMC 3292219. PMID 21325517.
  42. ^ Kübel, C.; Voigt, A.; Schoenmakers, R.; Otten, M.; Su, D.; Lee, TC.; Carlsson, A.; Bradley, J. (2005). "Recent Advances in Electron Tomography: TEM and HAADF-STEM Tomography for Materials Science and Semiconductor Applications". Microsc. Microanal. 11 (5): 378–400. Bibcode:2005MiMic..11..378K. doi:10.1017/S1431927605050361. OSTI 888597. PMID 17481320. S2CID 19979049.
  43. ^ Chan, S.; Li, P.; Locketz, G.; Salisbury, K.; Blevins, N.H. (2016). "High-fidelity haptic and visual rendering for patient-specific simulation of temporal bone surgery". Computer Assisted Surgery. 11 (1): 85–101. doi:10.1080/24699322.2016.1189966. PMID 2797394. S2CID 4028626.
  44. ^ a b Obenaus, A.; Hayes, P. (2011). "Drill Hole Defects: Induction, Imaging, and Analysis in the Rodent". Embryonic Stem Cell Therapy for Osteo-Degenerative Diseases. Methods in Molecular Biology. Vol. 690. pp. 301–314. doi:10.1007/978-1-60761-962-8_20. ISBN 978-1-60761-961-1. PMID 21043001.
  45. ^ Ertürk, A.; Mauch, C.P.; Hellal, F.; Förstner, F.; Keck, T.; Becker, K.; Jährling, N.; Steffens, H.; Richter, M.; Hübener, M.; Kramer, E.; Kirchhoff, F.; Dodt; Bradke, F. (2011). "Three-dimensional imaging of the unsectioned adult spinal cord to assess axon regeneration and glial responses after injury". Nature Medicine. 18 (1): 166–171. doi:10.1038/nm.2600. PMID 22198277. S2CID 16100638. Archived from the original on 2020-09-15. Retrieved 2019-12-03.
  46. ^ Carlson, K.J.; Wrangham, R.W.; Muller, M.N.; Sumner, D.R.; Morbeck, M.E.; Nishida, T.; Yamanaka, A.; Boesch, C. (2011). "Comparisons of Limb Structural Properties in Free-ranging Chimpanzees from Kibale, Gombe, Mahale, and Taï Communities". Primate Locomotion. pp. 155–182. doi:10.1007/978-1-4419-1420-0_9. ISBN 978-1-4419-1419-4. S2CID 12121244.
  47. ^ Hartwig, T.; Streitparth, F.; Gro, C.; Müller, M.; Perka, C.; Putzier, M.; Strube, P. (2011). "Digital 3-Dimensional Analysis of the Paravertebral Lumbar Muscles After Circumferential Single-level Fusion". Journal of Spinal Disorders & Techniques. 30 (6): E702–E706. doi:10.1097/BSD.0000000000000249. PMID 28632556. S2CID 4401218.
  48. ^ Lee, J.; Eddington, D.K.; Nadol, J.B. (2011). "The Histopathology of Revision Cochlear Implantation". Audiology and Neurotology. 16 (5): 336–346. doi:10.1159/000322307. PMC 7265424. PMID 21196725.
  49. ^ Han, M.; Kim, C.; Mozer, P.; Schafer, F.; Badaan, S.; Vigaru, B.; Tseng, K.; Petrisor, D.; Trock, B.; Stoianovici, D. (2011). "Tandem-robot Assisted Laparoscopic Radical Prostatectomy to Improve the Neurovascular Bundle Visualization: A Feasibility Study" (PDF). Urology. 77 (2): 502–6. doi:10.1016/j.urology.2010.06.064. PMC 3051397. PMID 21067797.

External links

source: http://en.wikipedia.org/wiki/Amira_(software)