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Towards Automatic Generation of 3D Models of Biological Objects Based on Serial Sections

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Visualization in Medicine and Life Sciences

Summary

We present a set of coherent methods for the nearly automatic creation of 3D geometric models from large stacks of images of histological sections. Three-dimensional surface models facilitate the visual analysis of 3D anatomy. They also form a basis for standardized anatomical atlases that allow researchers to integrate, accumulate and associate heterogeneous experimental information, like functional or gene-expression data, with spatial or even spatio-temporal reference. Models are created by performing the following steps: image stitching, slice alignment, elastic registration, image segmentation and surface reconstruction. The proposed methods are to a large extent automatic and robust against inevitably occurring imaging artifacts. The option of interactive control at most stages of the modeling process complements automatic methods.

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References

  1. A. MacKenzie-Graham et al. A Multimodal, Multidimensional Atlas of the C57BL/6J Mouse Brain. J. Anatomy, 204(2):93–102, 2004.

    Article  Google Scholar 

  2. D. Attali, D. Cohen-Steiner, and H. Edelsbrunner. Extraction and Simplification of Iso-surfaces in Tandem. In Symposium on Geometry Processing, pages 139-148, 2005.

    Google Scholar 

  3. M. Ahn, I. Guskov, and S. Lee. Out-of-core Remeshing of Large Polygonal Meshes. IEEE Transactions on Visualization and Computer Graphics, 12(5):1221–1228, 2006.

    Article  Google Scholar 

  4. C. Brüß, M. Strickert, and U. Seiffert. Towards Automatic Segmentation of Serial High-Resolution Images. In Proc. BVM Workshop, pages 126-130. Springer, 2006.

    Google Scholar 

  5. T. Czauderna and U. Seiffert. Implementation of MLP Networks Running Backpropagation on Various Parallel Computer Hardware Using MPI. In Ahmad Lotfi, editor, Proc. 5th Int. Conf. Recent Advances in Soft Computing (RASC), pages 116-121, 2004.

    Google Scholar 

  6. L. Nunes de Castro and F.J. Von Zuben. Recent Developments In Biologically Inspired Computing. Idea Group Publishing, Hershey, PA, USA, 2004.

    Google Scholar 

  7. V.J. Dercksen, S. Prohaska, and H.-C. Hege. Fast Cross-sectional Display of Large Data Sets. In IAPR Conf. Machine Vision Applications 2005, Japan, pages 336-339, 2005.

    Google Scholar 

  8. M. Dhenain, S.W. Ruffins, and R.E. Jacobs. Three-Dimensional Digital Mouse Atlas Using High-Resolution MRI. Developmental Biology, 232(2):458–470, 2001.

    Article  Google Scholar 

  9. B. Fischer and J. Modersitzki. Fast Inversion of Matrices Arising in Image Processing. Numerical Algorithms, 22:1–11, 1999.

    Article  MATH  MathSciNet  Google Scholar 

  10. N. Forbes. Imitation of Life - How Biology is Inspiring Computing. The MIT Press, Cambridge, MA, USA, 2004.

    Google Scholar 

  11. M. Garland and P.S. Heckbert. Surface Simplification Using Quadric Error Metrics. In SIGGRAPH’97 Conf. Proc., pages 209-216, 1997.

    Google Scholar 

  12. S.M. Glidewell. NMR Imaging of Developing Barley Grains. J. Cereal Science, 43:70–78, 2006.

    Article  Google Scholar 

  13. R.C. Gonzalez and R.E. Woods. Digital Image Processing. Prentice-Hall, Upper Sadle River, New Jersey, 2nd ed. edition, 2002.

    Google Scholar 

  14. H.-C. Hege et al. A Generalized Marching Cubes Algorithm Based on Non-Binary Classifications. Technical report, ZIB Preprint SC-97-05, 1997.

    Google Scholar 

  15. J. Haseloff. Old Botanical Techniques for New Microscopes. Biotechniques, 34:1174–1182, 2003.

    Google Scholar 

  16. B. Hammer, M. Strickert, and T. Villmann. Supervised Neural Gas with General Similarity Measure. Neural Processing Letters, 21(1):21–44, 2005.

    Article  Google Scholar 

  17. J.C. Mazziotta et al. Atlases of the Human Brain. In S.H. Koslow and M.F. Huerta, editors, Neuroinformatics - An overview of the human brain project, pages 255-308, 1997.

    Google Scholar 

  18. J.F. Brinkley et al. Design of an Anatomy Information System. Computer Graphics and Applications, 19(3):38–48, 1999.

    Article  Google Scholar 

  19. J.P. Carson et al. A Digital Atlas to Characterize the Mouse Brain Transcriptome. PLoS Computational Biology, 1(4), 2005.

    Google Scholar 

  20. J.T. Johnson et al. Virtual Histology of Transgenic Mouse Embryos for High-Throughput Phenotyping. PLos Genet, 2(4):doi: 10.1371/jour-nal.pgen.0020061, 2006.

    Google Scholar 

  21. T. Ju. Building a 3D Atlas of the Mouse Brain. PhD thesis, Rice University, April 2005.

    Google Scholar 

  22. K. H. Höhne et al. A 3D Anatomical Atlas Based on a Volume Model. IEEE Computer Graphics Applications, 12(4):72–78, 1992.

    Article  Google Scholar 

  23. K. Lee et al. Visualizing Plant Development and Gene Expression in Three Dimensions Using Optical Projection Tomography. The Plant Cell, 18:2145–2156, 2006.

    Article  Google Scholar 

  24. H. Kuensting, Y. Ogawa, and J. Sugiyama. Structural Details in Soybeans: A New Three-dimensional Visualization Method. J. Food Science, 67(2):721–72, 2002.

    Article  Google Scholar 

  25. W.E. Lorensen and H.E. Cline. Marching Cubes: A High Resolution 3D Surface Construction Algorithm. In Proc. ACM SIGGRAPH’87, volume 21(4), pages 1631-169, 1987.

    Google Scholar 

  26. E.C. LaMar, B. Hamann, and K.I. Joy. Multiresolution techniques for interactive texture-based volume visualization. In David S. Ebert, Markus Gross, and Bernd Hamann, editors, IEEE Visualization ’99, pages 355-361, Los Alamitos, California, 1999. IEEE, IEEE Computer Society Press.

    Google Scholar 

  27. R. P. Lippmann. An Introduction to Computing with Neural Nets. IEEE ASSP Magazine, 4(87):4–23, 1987.

    Article  Google Scholar 

  28. C. Levinthal and R. Ware. Three Dimensional Reconstruction from Serial Sections. Nature, 236:207–210, 1972.

    Article  Google Scholar 

  29. M.H. Kaufman et al. Computer-Aided 3-D Reconstruction of Serially Sectioned Mouse Embryos: Its Use in Integrating Anatomical Organization. Int’l J. Developmental Biology, 41(2):223–33, 1997.

    Google Scholar 

  30. J. Modersitzki. Numerical Methods for Image Registration. Oxford University Press, New York, 2004.

    MATH  Google Scholar 

  31. M. Minsky and S. Papert. Perceptrons: An Introduction to Computational Geometry. MIT Press, Cambridge, 1969.

    MATH  Google Scholar 

  32. K. Montgomery and M.D. Ross. Improvements in semiautomated serial-section reconstruction and visualization of neural tissue from TEM images. In SPIE Electronic Imaging, 3D Microscopy conf. proc., pages 264-267, 1994.

    Google Scholar 

  33. J. Maintz and M. Viergever. A Survey of Medical Image Registration. Medical Image Analysis, 2(1):1–36, 1998.

    Article  Google Scholar 

  34. W. Pereanu and V. Hartenstein. Digital Three-Dimensional Models of Drosophila Development. Current Opinion in Genetics & Development, 14(4):382–391, 2004.

    Article  Google Scholar 

  35. R. Baldock et al. EMAP and EMAGE: A Framework for Understanding Spatially Organized Data. Neuroinformatics, 1(4):309–325, 2003.

    Article  Google Scholar 

  36. R. Brandt et al. A Three-Dimensional Average-Shape Atlas of the Honeybee Brain and its Applications. J. Comparative Neurology, 492(1):1–19, 2005. 24V.J. Dercksen et al.

    Article  Google Scholar 

  37. D. E. Rumelhart, G. E. Hinton, and R. J. Williams. Learning Internal Representations by Error Propagation. In D. E. Rumelhart et al., editor, Parallel Distributed Processing: Explorations in the Microstructure of Cognition, pages 318–362, Cambridge, 1986. MIT Press.

    Google Scholar 

  38. K. Rein, M. Zöckler, and M. Heisenberg. A Quantitative Three-Dimensional Model of the Drosophila Optic Lobes. Current Biology, 9:93–96, 1999.

    Article  Google Scholar 

  39. S. Wirtz et al. Super-Fast Elastic Registration of Histologic Images of a Whole Rat Brain for Three-Dimensional Reconstruction. In Proc. SPIE 2004, Medical Imaging, 2004.

    Google Scholar 

  40. S. Gubatz et al. Three-Dimensional Digital Models of Developing Barley Grains for the Visualisation of Expression Patterns. In prep., 2007.

    Google Scholar 

  41. U. Seiffert. Artificial Neural Networks on Massively Parallel Computer Hardware. Neurocomputing, 57:135–150, 2004.

    Article  Google Scholar 

  42. M. Sonka, V. Hlavac, and R. Boyle. Image Processing, Analysis, and Machine Vision. Brooks//Cole Publishing Company, Upper Sadle River, New Jersey, 2nd ed. edition, 1999.

    Google Scholar 

  43. C. Studholme, D. L. G. Hill, and D. J. Hawkes. Automated Three-Dimensional Registration of Magnetic Resonance and Positron Emission Tomography Brain Images by Multiresolution Optimization of Voxel Similarity Measures. Medical Physics, 24(1):25–35, 1997.

    Article  Google Scholar 

  44. G. Subsol, J.-Ph. Thirion, and N. Ayache. Some Applications of an Automatically Built 3D Morphometric Skull Atlas. In Computer Assisted Radiology, pages 339-344, 1996.

    Google Scholar 

  45. J.A.K. Suykens, J.P.L. Vandewalle, and B.L.R. De Moor. Artificial Neural Networks for Modelling and Control of Non-Linear Systems. Kluwer Academic Publishers, Den Haag, The Netherlands, 1996.

    Google Scholar 

  46. D. Stalling, M. Westerhoff, and H. C. Hege. Amira - a Highly Interactive System for Visual Data Analysis. In C.D. Hansen and C.R. Johnson, editors, Visualization Handbook, pages 749-767. Elsevier, 2005.

    Google Scholar 

  47. J. Streicher, W.J. Weninger, and G.B. Müller. External Marker-Based Automatic Congruencing: A New Method of 3D Reconstruction from Serial Sections. The Anatomical Record, 248(4):583–602, 1997.

    Article  Google Scholar 

  48. R. Szeliski. Image Alignment and Stitching. In N. Paragios, Y. Chen, and O. Faugeras, editors, Handbook of Mathematical Models in Computer Vision, pages 273-292. Springer, 2005.

    Google Scholar 

  49. T. Ju et al. 3D volume reconstruction of a mouse brain from histological sections using warp filtering. J. of Neuroscience Methods, 156:84–100, 2006.

    Article  Google Scholar 

  50. U.D. Braumann et al. Three-Dimensional Reconstruction and Quantification of Cervical Carcinoma Invasion Fronts from Histological Serial Sections. IEEE Transactions on Medical Imaging, 24(10):1286–1307, 2005.

    Article  Google Scholar 

  51. M. Westerhoff. Efficient Visualization and Reconstruction of 3D Geometric Models from Neuro-Biological Confocal Microscope Scans. Phd thesis, Fachbereich Mathematik und Informatik, Freie Universität Berlin, Jan. 2003.

    Google Scholar 

  52. R.T. Whitaker. Reducing Aliasing Artifacts in Iso-Surfaces of Binary Volumes. In Proc. 2000 IEEE Symposium on Volume Visualization, pages 23-32. ACM Press, 2000.

    Google Scholar 

  53. J. Wu and L. Kobbelt. A Stream Algorithm for the Decimation of Massive Meshes. In Graphics Interface’03 Conf. Proc., 2003.

    Google Scholar 

  54. Y. Ogawa et al. Advanced Technique for Three-Dimensional Visualization of Compound Distributions in a Rice Kernel. J. Agricultural and Food Chemistry, 49(2):736–740, 2001.

    Article  Google Scholar 

  55. B. Zitova and J. Flusser. Image registration methods: a survey. Image and Vision Computing, 21(11):977–1000, October 2003.

    Article  Google Scholar 

  56. M. Zilske, H. Lamecker, and S. Zachow. Remeshing of non-manifold surfaces. ZIB-Report 07-01, In prep., 2007.

    Google Scholar 

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Dercksen, V., Brüß, C., Stalling, D., Gubatz, S., Seiffert, U., Hege, HC. (2008). Towards Automatic Generation of 3D Models of Biological Objects Based on Serial Sections. In: Linsen, L., Hagen, H., Hamann, B. (eds) Visualization in Medicine and Life Sciences. Mathematics and Visualization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72630-2_1

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