Abstract
A variety of biological samples can be imaged by the atomic force microscope (AFM) under environments that range from vacuum to ambient to liquid. Generally imaging is pursued to evaluate structural features of the sample or perhaps identify some structural changes in the sample that are induced by the investigator. In many cases, AFM images of sample features and induced structural changes are interpreted in general qualitative terms such as markedly smaller or larger, rougher, highly irregular, or smooth. Various manual tools can be used to analyze images and extract more quantitative data, but this is usually a cumbersome process. To facilitate quantitative AFM imaging, automated image analysis routines are being developed. Viral particles imaged in water were used as a test case to develop an algorithm that automatically extracts average dimensional information from a large set of individual particles. The extracted information allows statistical analyses of the dimensional characteristics of the particles and facilitates interpretation related to the binding of the particles to the surface. This algorithm is being extended for analysis of other biological samples and physical objects that are imaged by AFM.
| Original language | English |
|---|---|
| Pages (from-to) | 829-837 |
| Number of pages | 9 |
| Journal | Ultramicroscopy |
| Volume | 106 |
| Issue number | 8-9 |
| DOIs | |
| State | Published - Jun 2006 |
Funding
This research was funded by the Laboratory Directed Research and Development Program of Oak Ridge National Laboratory (ORNL), US DOE Office of Biological and Environmental Sciences Medical Sciences Division, and by NIH grant R01 AI-57933 to JEC. Oak Ridge National Laboratory is managed by UT-Battelle, LLC, for the US Department of Energy under Contract No. DE-AC05-00OR22725.
Keywords
- 005
- 014
- 018
- 025
- Atomic force microscopy
- Automated image analysis
- Feature extraction
- Rotavirus particles.