Hostname: page-component-848d4c4894-p2v8j Total loading time: 0.001 Render date: 2024-05-23T14:35:01.625Z Has data issue: false hasContentIssue false
  • English
  • Français

Theta Rotation and Serial Registration of Light Microscopical Images Using a Novel Camera Rotating Device

Published online by Cambridge University Press:  17 March 2010

Bradley S. Duerstock ,
John Cirillo  and
Bartek Rajwa
Bradley S. Duerstock*
Affiliation:
Center for Paralysis Research, School of Veterinary Medicine, Purdue University, West Lafayette, IN 47907, USA
John Cirillo
Affiliation:
Center for Paralysis Research, School of Veterinary Medicine, Purdue University, West Lafayette, IN 47907, USA
Bartek Rajwa
Affiliation:
Purdue UniversityCytometry Laboratories, Bindley Bioscience Center, Purdue University, West Lafayette, IN 47907, USA
*
Corresponding author. E-mail: bsd@purdue.edu
Get access

Abstract

An electromechanical video camera coupler was developed to rotate a light microscope field of view (FOV) in real time without the need to physically rotate the stage or specimen. The device, referred to as the Camera Thetarotator, rotated microscopical views 240° to assist microscopists to orient specimens within the FOV prior to image capture. The Camera Thetarotator eliminated the effort and artifacts created when rotating photomicrographs using conventional graphics software. The Camera Thetarotator could also be used to semimanually register a dataset of histological sections for three-dimensional (3D) reconstruction by superimposing the transparent, real-time FOV to the previously captured section in the series. When compared to Fourier-based software registration, alignment of serial sections using the Camera Thetarotator was more exact, resulting in more accurate 3D reconstructions with no computer-generated null space. When software-based registration was performed after prealigning sections with the Camera Thetarotator, registration was further enhanced. The Camera Thetarotator expanded microscopical viewing and digital photomicrography and provided a novel, accurate registration method for 3D reconstruction. The Camera Thetarotator would also be useful for performing automated microscopical functions necessary for telemicroscopy, high-throughput image acquisition and analysis, and other light microscopy applications.

Keywords

light microscopyphotomicrographydigital video cameratheta rotationimage acquisitionserial section registration3D reconstruction
Type
Instrumentation and Software: Development and Applications
Information
Microscopy and Microanalysis , Volume 16 , Issue 3 , June 2010 , pp. 239 - 247
Copyright
Copyright © Microscopy Society of America 2010

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

Allen, B.A. & Levinthal, C. (1990). CARTOS II semi-automated nerve tracing: Three-dimensional reconstruction from serial section micrographs. Comput Med Imaging Graph 14, 319–329.CrossRefGoogle ScholarPubMed
Arganda-Carreras, I., Sorzano, C.O.S., Marabini, R., Carazo, J.M., Ortiz-de-Solorzano, C. & Kybic, J. (2006). Consistent and elastic registration of histological sections using vector-spline regularization. In Computer Vision Approaches to Medical Image Analysis, Beichel, R. & Sonka, M. (Eds.), pp. 85–95. Heidelberg, Berlin: Springer.CrossRefGoogle Scholar
Bron, C., Gremillet, P., Launay, D., Jourlin, M., Gautschi, H.P., Bachi, T. & Schupbach, J. (1990). Three-dimensional electron microscopy of entire cells. J Microsc 157, 115–126.CrossRefGoogle ScholarPubMed
Deverell, M.H., Salisbury, J.R., Cookson, M.J., Holman, J.G., Dykes, E. & Whimster, W.F. (1993). Three-dimensional reconstruction: Methods of improving image registration and interpretation. Anal Cell Pathol 5, 253–263.Google ScholarPubMed
Duerstock, B.S. (2004). Double labeling serial sections to enhance three-dimensional imaging of injured spinal cord. J Neurosci Methods 134, 101–107.CrossRefGoogle ScholarPubMed
Duerstock, B.S., Bajaj, C.L. & Borgens, R.B. (2003). A comparative study of the quantitative accuracy of three-dimensional reconstructions of spinal cord from serial histological sections. J Microsc 210, 138–148.CrossRefGoogle ScholarPubMed
Duerstock, B.S., Bajaj, C.L., Pascucci, V., Schikore, D., Lin, K.N. & Borgens, R.B. (2000). Advances in three-dimensional reconstruction of the experimental spinal cord injury. Comput Med Imaging Graph 24, 389–406.CrossRefGoogle ScholarPubMed
Hibbard, L.S., Grothe, R.A. Jr., Arnicar-Sulze, T.L., Dovey-Hartman, B.J. & Page, R.B. (1993). Computed three-dimensional reconstruction of median-eminence capillary modules: Image alignment and correlation. J Microsc 171, 39–56.CrossRefGoogle ScholarPubMed
Honghui, G. & Qunsheng, P. (1996). Efficient alignment algorithm for 3D reconstruction of pulmonary alveolus from serial microsections. In Fourth International Conference on Computer-Aided Design and Computer Graphics, Yang, S., Zhou, J. & Li, C.-G. (Eds.), pp. 62–68. Bellingham, WA: SPIE.Google Scholar
Kawata, M. & Sato, C. (2007). A statistically harmonized alignment-classification in image space enables accurate and robust alignment of noisy images in single particle analysis. J Electron Microsc (Tokyo) 56, 83–92.CrossRefGoogle ScholarPubMed
Martone, M.E., Zhang, Y., Simpliciano, V.M., Carragher, B.O. & Ellisman, M.H. (1993). Three-dimensional visualization of the smooth endoplasmic reticulum in Purkinje cell dendrites. J Neurosci 13, 4636–4646.CrossRefGoogle ScholarPubMed
Montgomery, K.N. & Ross, M.D. (1993). Method for semiautomated serial section reconstruction and visualization of neural tissue from TEM images. In Conference on Biomedical Image Processing and Biomedical Visualization, Raj, S.A. & Dmitry, B.G. (Eds.), pp. 114–120. Bellingham, WA: SPIE.CrossRefGoogle Scholar
Moriarty, L.J., Duerstock, B.S., Bajaj, C.L., Lin, K. & Borgens, R.B. (1998). Two- and three-dimensional computer graphic evaluation of the subacute spinal cord injury. J Neurol Sci 155, 121–137.CrossRefGoogle ScholarPubMed
Prothero, J.S. & Prothero, J.W. (1986). Three-dimensional reconstruction from serial sections. IV. The reassembly problem. Comput Biomed Res 19, 361–373.CrossRefGoogle ScholarPubMed
Roesch, S., Mailly, P., Deniau, J.M. & Maurin, Y. (1996). Computer assisted three-dimensional reconstruction of brain regions from serial section digitized images. Application to the organization of striato-nigral relationships in the rat. J Neurosci Methods 69, 197–204.CrossRefGoogle Scholar
Sorzano, C.O., Messaoudi, C., Eibauer, M., Bilbao-Castro, J.R., Hegerl, R., Nickell, S., Marco, S. & Carazo, J.M. (2009). Marker-free image registration of electron tomography tilt-series. BMC Bioinformatics 10, 124.CrossRefGoogle ScholarPubMed
Sorzano, C.O.S., Thevenaz, P. & Unser, M. (2005). Elastic registration of biological images using vector-spline regularization. EEE Trans Biomed Eng 52, 652–663.CrossRefGoogle ScholarPubMed
Toga, A.W. (1990). Three-dimensional reconstruction. In Three-Dimensional Neuroimaging, Toga, A.W. (Ed.), pp. 1–50. New York: Raven Press.Google Scholar
Vuillemin, M., Pexieder, T., Wong, Y.M. & Thompson, R.P. (1992). A two-step alignment method for 3D computer-aided reconstruction based on fiducial markers and applied to mouse embryonic hearts. Eur J Morphol 30, 181–193.Google ScholarPubMed
Williams, B.S. & Doyle, M.D. (1996). An Internet atlas of mouse development. Comput Med Imaging Graph 20, 433–447.CrossRefGoogle ScholarPubMed
Wu, Q., Merchant, F. & Castleman, K. (2008). Microscope Image Processing. New York: Academic Press.Google Scholar
Yang, S., Köhler, D., Teller, K., Cremer, T., Le Baccon, P., Heard, E., Eils, R. & Rohr, K. (2008). Non-rigid registration of 3-D multichannel microscopy images of cell nuclei. IEEE Trans Image Processing 17, 493–499.CrossRefGoogle Scholar