Molecular Imaging and Biology

, Volume 17, Issue 1, pp 18–28 | Cite as

A Deformable Atlas of the Laboratory Mouse

  • Hongkai WangEmail author
  • David B. Stout
  • Arion F. Chatziioannou
Research Article



This paper presents a deformable mouse atlas of the laboratory mouse anatomy. This atlas is fully articulated and can be positioned into arbitrary body poses. The atlas can also adapt body weight by changing body length and fat amount.


A training set of 103 micro-CT images was used to construct the atlas. A cage-based deformation method was applied to realize the articulated pose change. The weight-related body deformation was learned from the training set using a linear regression method. A conditional Gaussian model and thin-plate spline mapping were used to deform the internal organs following the changes of pose and weight.


The atlas was deformed into different body poses and weights, and the deformation results were more realistic compared to the results achieved with other mouse atlases. The organ weights of this atlas matched well with the measurements of real mouse organ weights. This atlas can also be converted into voxelized images with labeled organs, pseudo CT images and tetrahedral mesh for phantom studies.


With the unique ability of articulated pose and weight changes, the deformable laboratory mouse atlas can become a valuable tool for preclinical image analysis.

Key words

Small animal imaging Mouse atlas Articulated model Atlas registration Molecular imaging 



The authors thank Dr. Richard M. Leahy and Dr. Boudewijn P.F. Lelieveldt for providing the online resources of the Digimouse atlas and the articulated mouse skeleton atlas and Dr. Qianqian Fang and Dr. Bing Jian for publishing the software of iso2mesh and point set registration. We thank Dr. Anna Wu, Owen Witte, Tove Olafsen, Melissa Mccracken, Richard Tavare, Scott Knowles, Waldemar Ladno, and Darin Williams from UCLA for sharing the mouse organ weight dissection data and Dr. John David, D.V.M. for the professional comments on mouse anatomy. We also appreciate the efforts of the anonymous reviewers who helped us to improve the paper quality. This work was supported in part by SAIRP NIHNCI 2U24 CA092865 and a UCLA Chancellor’s Bioscience Core grant.

Conflict of Interest

This deformable mouse atlas contains copyrightable subject matter that has been assigned to the Regents of the University of California (UC case 2014-894).

Supplementary material


(MP4 8.75 mb)


  1. 1.
    Dogdas B, Stout D, Chatziioannou AF, Leahy RM (2007) Digimouse: a 3D whole body mouse atlas from CT and cryosection data. Phys Med Biol 52:577–587PubMedCentralPubMedCrossRefGoogle Scholar
  2. 2.
    Segars WP, Tsui BMW, Frey EC et al (2004) Development of a 4-D digital mouse phantom for molecular imaging research. Mol Imag Biol 6:149–159CrossRefGoogle Scholar
  3. 3.
    Johnson GA, Cofer GP, Gewalt SL, Hedlund LW (2002) Morphologic phenotyping with MR microscopy: the visible mouse. Radiology 222:789–793PubMedCrossRefGoogle Scholar
  4. 4.
    ITIS Foundation. ITIS Virtual Population animal models.
  5. 5.
    Khmelinskii A, Baiker M, Kaijzel EL et al (2011) Articulated whole-body atlases for small animal image analysis: construction and applications. Mol Imag Biol 13:898–910CrossRefGoogle Scholar
  6. 6.
    Clark D, Badea A, Johnson GA, Badea CT (2013) Constructing a 4D murine cardiac micro-CT atlas for automated segmentation and phenotyping applications. Proc SPIE Med Imaging 8669:1–12Google Scholar
  7. 7.
    Fiebig T, Boll H, Figueiredo G et al (2012) Three-dimensional in vivo imaging of the murine liver: a micro-computed tomography-based anatomical study. PLoS One 7:e31179PubMedCentralPubMedCrossRefGoogle Scholar
  8. 8.
    Ólafsdóttir H, Darvann TA, Hermann NV et al (2007) Computational mouse atlases and their application to automatic assessment of craniofacial dysmorphology caused by the Crouzon mutation Fgfr2C342Y. J Anat 211:37–52PubMedCentralPubMedCrossRefGoogle Scholar
  9. 9.
    DeLaurier A, Burton N, Bennett M et al (2008) The mouse limb anatomy atlas: an interactive 3D tool for studying embryonic limb patterning. BMC Dev Biol 8:83PubMedCentralPubMedCrossRefGoogle Scholar
  10. 10.
    Wang H, Stout DB, Chatziioannou AF (2012) Estimation of mouse organ locations through registration of a statistical mouse atlas with micro-CT images. IEEE Trans Med Imag 31:88–102CrossRefGoogle Scholar
  11. 11.
    Dhenain M, Ruffins SW, Jacobs RE (2001) Three-dimensional digital mouse atlas using high-resolution MRI. Dev Biol 232:458–470PubMedCrossRefGoogle Scholar
  12. 12.
    Kovacevic N, Henderson JT, Chan E et al (2005) A three-dimensional MRI atlas of the mouse brain with estimates of the average and variability. Cereb Cortex 15:639–645PubMedCrossRefGoogle Scholar
  13. 13.
    Badea A, Gewalt S, Avants BB et al (2012) Quantitative mouse brain phenotyping based on single and multispectral MR protocols. Neuroimage 63:1633–1645PubMedCentralPubMedCrossRefGoogle Scholar
  14. 14.
    Jiang Y, Johnson GA (2011) Microscopic diffusion tensor atlas of the mouse brain. Neuroimage 56:1235–1243PubMedCentralPubMedCrossRefGoogle Scholar
  15. 15.
    Bertrand L, Nissanov J (2008) The neuroterrain 3D mouse brain atlas. Fron Neuroinform 2:3CrossRefGoogle Scholar
  16. 16.
    Ju T, Warren J, Eichele G et al (2003) A geometric database for gene expression data. Symp Geom Process 2003:166–176PubMedCentralPubMedGoogle Scholar
  17. 17.
    High resolution mouse brain atlas.
  18. 18.
    Jones AR, Overly CC, Sunkin SM (2009) The Allen brain atlas: 5 years and beyond. Nat Rev Neurosci 10:821–828PubMedCrossRefGoogle Scholar
  19. 19.
    Rosen GD, La Porte NT, Diechtiareff B et al (2003) Informatics center for mouse genomics: the dissection of complex traits of the nervous system. Neuroinformatics 1:327PubMedCrossRefGoogle Scholar
  20. 20.
    Lee EF, Boline J, Toga AW (2007) A high-resolution anatomical framework of the neonatal mouse brain for managing gene expression data. Front Neuroinform 1:6PubMedCentralPubMedGoogle Scholar
  21. 21.
    Li A, Gong H, Zhang B et al (2010) Micro-optical sectioning tomography to obtain a high-resolution atlas of the mouse brain. Science 330:1404–1408PubMedCrossRefGoogle Scholar
  22. 22.
    Hawrylycz M, Baldock RA, Burger A et al (2011) Digital atlasing and standardization in the mouse brain. PLoS Comput Biol 7Google Scholar
  23. 23.
    Mackenzie-Graham AJ, Lee EF, Dinov ID et al (2007) Multimodal, multidimensional models of mouse brain. Epilepsia 48(Suppl 4):75–81PubMedCentralPubMedCrossRefGoogle Scholar
  24. 24.
    Burger A, Davidson D, Baldock R, et al. (2008) The Edinburgh mouse atlas. In: Anatomy ontologies for bioinformatics, vol. 6. Springer, London, pp. 249–265.Google Scholar
  25. 25.
    Richardson L, Stevenson P, Venkataraman S et al (2014) EMAGE: electronic mouse atlas of gene expression. Methods Mol Biol 1092:61–79PubMedCrossRefGoogle Scholar
  26. 26.
    Jacobs RE, Ahrens ET, Dickinson ME, Laidlaw D (1999) Towards a microMRI atlas of mouse development. Comput Med Imaging Graph 23:15–24PubMedCrossRefGoogle Scholar
  27. 27.
    Wong MD, Dorr AE, Walls JR et al (2012) A novel 3D mouse embryo atlas based on micro-CT. Development 139:3248–3256PubMedCrossRefGoogle Scholar
  28. 28.
    Baiker M, Milles J, Dijkstra J et al (2010) Atlas-based whole-body segmentation of mice from low-contrast Micro-CT data. Med Image Anal 14:723–737PubMedCrossRefGoogle Scholar
  29. 29.
    Khmelinskii A, Baiker M, Chen XJ, et al. (2010) Atlas-based organ & bone approximation for ex-vivo MRI mouse data: a pilot study. Proceedings of the 7th IEEE international symposium on biomedical imaging: from nano to macro, 1197–1200.Google Scholar
  30. 30.
    Khmelinskii A, Groen HC, Baiker M et al (2012) Segmentation and visual analysis of whole-body mouse skeleton microSPECT. PLoS One 7:e48976PubMedCentralPubMedCrossRefGoogle Scholar
  31. 31.
    Kesner AL, Dahlbom M, Huang SC et al (2006) Semiautomated analysis of small-animal PET data. J Nucl Med 47:1181–1186PubMedGoogle Scholar
  32. 32.
    Wang H, Stout DB, Taschereau R et al (2012) MARS: a mouse atlas registration system based on planar x-ray projector and optical camera. Phys Med Biol 57:6063–6077PubMedCentralPubMedCrossRefGoogle Scholar
  33. 33.
    Wang H Stout DB Olafsen T and Chatziioannou AF (2011) Quantification of organ uptake from small animal PET images via registration with a statistical mouse atlas. Proceedings of the medical image computing and computer-assisted intervention (MICCAI), workshop on multi-atlas labeling and statistical fusion, 11–18.Google Scholar
  34. 34.
    Song X, Wang D, Chen N et al (2007) Reconstruction for free-space fluorescence tomography using a novel hybrid adaptive finite element algorithm. Opt Express 15:18300–18317PubMedCrossRefGoogle Scholar
  35. 35.
    Ren S, Chen X, Wang H et al (2013) Molecular optical simulation environment (MOSE): a platform for the simulation of light propagation in turbid media. PLoS One 8:e61304PubMedCentralPubMedCrossRefGoogle Scholar
  36. 36.
    Xie T, Zaidi H (2013) Monte Carlo-based evaluation of S-values in mouse models for positron-emitting radionuclides. Phys Med Biol 58:169–182PubMedCrossRefGoogle Scholar
  37. 37.
    Gu Z, Taschereau R, Vu NT et al (2013) NEMA NU-4 performance evaluation of PETbox4, a high sensitivity dedicated PET preclinical tomograph. Phys Med Biol 58:3791–3814PubMedCentralPubMedCrossRefGoogle Scholar
  38. 38.
    ITIS Foundation. SEMCAD X numerical phantoms.
  39. 39.
    Snoeks TJ, Baiker M, Kaijzel EL et al (2012) CT-based handling and analysis of preclinical multimodality imaging data of bone metastases. Boneke Rep 1:79CrossRefGoogle Scholar
  40. 40.
    Baiker M, Staring M, Löwik CWGM et al (2011) Automated registration of whole-body follow-up MicroCT data of mice. Proc Med Image Comput Comput-Assist Interv-MICCAI 6892:516–523Google Scholar
  41. 41.
    Henkelman RM (2010) Systems biology through mouse imaging centers: experience and new directions. Annu Rev Biomed Eng 12:143–166PubMedCrossRefGoogle Scholar
  42. 42.
    Suckow C, Stout D (2008) MicroCT liver contrast agent enhancement over time, dose, and mouse strain. Mol Imag Biol 10:114–120CrossRefGoogle Scholar
  43. 43.
    Stout D, Chatziioannou A, Lawson T et al (2005) Small animal imaging center design: the facility at the UCLA Crump Institute for Molecular Imaging. Mol Imag Biol 7:393–402CrossRefGoogle Scholar
  44. 44.
    Bing J, Vemuri BC (2005) A robust algorithm for point set registration using mixture of Gaussians. Proc IEEE Int Conf Comput Vis (ICCV 2005) 2:1246–1251Google Scholar
  45. 45.
    Lewis JP, Cordner M, and Fong N (2000) Pose space deformation: a unified approach to shape interpolation and skeleton-driven deformation. Proceedings of the 27th annual conference on Computer graphics and interactive techniques, 165–172.Google Scholar
  46. 46.
    Jacka D, Reid A, Merry B, and Gain J (2007) A comparison of linear skinning techniques for character animation. Proceedings of the 5th international conference on computer graphics, virtual reality, visualisation and interaction in Africa, 177–186.Google Scholar
  47. 47.
    Anguelov D, Srinivasan P, Koller D et al (2005) Scape: shape completion and animation of people. Proc ACM Trans Graph (TOG) 24:408–416CrossRefGoogle Scholar
  48. 48.
    Hasler N, Stoll C, Sunkel M et al (2009) A statistical model of human pose and body shape. Proc Comput Graph Forum 28:337–346CrossRefGoogle Scholar
  49. 49.
    Brett A, Brian C, Zoran P (2003) The space of human body shapes: reconstruction and parameterization from range scans. ACM Trans Graph 22:587–594CrossRefGoogle Scholar
  50. 50.
    Wilhelms J (1995) Modeling animals with bones, muscles, and skin. Citeseer.Google Scholar
  51. 51.
    Joshi P, Meyer M, DeRose T et al (2007) Harmonic coordinates for character articulation. Proc ACM Transactions on Graphics (TOG) 26:71CrossRefGoogle Scholar
  52. 52.
    Baran I, Popovi’c J (2007) Automatic rigging and animation of 3D characters. Proc ACM Transactions on Graphics (TOG) 26:72CrossRefGoogle Scholar
  53. 53.
    Hastings IM, Yang J, Hill WG (1991) Analysis of lines of mice selected on fat content. 4. Correlated responses in growth and reproduction. Genet Res 58:253–259PubMedCrossRefGoogle Scholar
  54. 54.
    Bergmann P, Militzer K, Schmidt P, Buttner D (1995) Sex differences in age development of a mouse inbred strain: body composition, adipocyte size and organ weights of liver, heart and muscles. Lab Anim 29:102–109PubMedCrossRefGoogle Scholar
  55. 55.
    Weber O, Sorkine O, Lipman Y, Gotsman C (2007) Context-aware skeletal shape deformation. Proc Computer Graphics Forum 26:265–274CrossRefGoogle Scholar
  56. 56.
    Wang H, Stout DB, Chatziioannou AF (2013) A method of 2D/3D registration of a statistical mouse atlas with a planar X-ray projection and an optical photo. Med Image Anal 17:401–416PubMedCentralPubMedCrossRefGoogle Scholar
  57. 57.
    Savinaud M, de La Gorce M, Maitrejean S, Paragios N (2010) Model-based multi-view fusion of cinematic flow and optical imaging. Med Image Comput Comput Assist Interv 13:668–675PubMedGoogle Scholar
  58. 58.
    Eisen EJ (2005) The mouse in animal genetics and breeding research. Imperial College Press, London.Google Scholar
  59. 59.
    Reed DR, Bachmanov AA, Tordoff MG (2007) Forty mouse strain survey of body composition. Physiol Behav 91:593–600PubMedCentralPubMedCrossRefGoogle Scholar
  60. 60.
    Woglom WH (1919) The size of the spleen in immune mice. J Cancer Res 4:281–323Google Scholar
  61. 61.
    Fang Q and Boas DA (2009) Tetrahedral mesh generation from volumetric binary and grayscale images. Proceedings of the biomedical imaging: from nano to macro, 2009 ISBI ’09 IEEE international symposium on, 1142–1145.Google Scholar

Copyright information

© Academy of Molecular Imaging and Society for Molecular Imaging 2014

Authors and Affiliations

  • Hongkai Wang
    • 1
    Email author
  • David B. Stout
    • 1
  • Arion F. Chatziioannou
    • 1
  1. 1.Crump Institute of Molecular Imaging, David Geffen School of MedicineUCLALos AngelesUSA

Personalised recommendations