Back to Search
Start Over
Template matching as a tool for annotation of tomograms of stained biological structures
- Source :
- Journal of Structural Biology, 158(3), 327. Academic Press Inc.
- Publication Year :
- 2007
- Publisher :
- Elsevier BV, 2007.
-
Abstract
- In recent years, electron tomography has improved our three-dimensional (3D) insight in the structural architecture of cells and organelles. For studies that involve the 3D imaging of stained sections, manual annotation of tomographic data has been an important method to help understand the overall 3D morphology of cellular compartments. Here, we postulate that template matching can provide a tool for more objective annotation and contouring of cellular structures. Also, this technique can extract information hitherto unharvested in tomographic studies. To evaluate the performance of template matching on tomograms of stained sections, we generated several templates representing a piece of microtubule or patches of membranes of different staining-thicknesses. These templates were matched to tomograms of stained electron microscopy sections. Both microtubules and ER-Golgi membranes could be detected using this method. By matching cuboids of different thicknesses, we were able to distinguish between coated and non-coated endosomal membrane-domains. Finally, heterogeneity in staining-thickness of endosomes could be observed. Template matching can be a useful addition to existing annotation-methods, and provide additional insights in cellular architecture. © 2006 Elsevier Inc. All rights reserved.
- Subjects :
- Cell biology
Matching (statistics)
Molecular biology
Golgi Apparatus
Image processing
Biology
Endoplasmic Reticulum
Microtubules
Imaging, Three-Dimensional
Biologie/Milieukunde (BIOL)
Microscopy, Electron, Transmission
Structural Biology
Humans
Computer vision
Contouring
Staining and Labeling
Cellular architecture
business.industry
Template matching
Cell Membrane
Pattern recognition
Life sciences
Template
Electron tomography
International (English)
Artificial intelligence
Tomography
business
Subjects
Details
- ISSN :
- 10478477
- Volume :
- 158
- Database :
- OpenAIRE
- Journal :
- Journal of Structural Biology
- Accession number :
- edsair.doi.dedup.....dc9d45b7c52f2e40255dae3f5c45b8dd