Imaging Protocols
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='''Variations in staining: '''= | ='''Variations in staining: '''= | ||
| − | The hardest first step in computational image analysis is segmentation - the delineation of structures in images. This task would be very easy if the structures of interest were uniformly stained. | + | The hardest first step in computational image analysis is segmentation - the delineation of structures in images. This task would be very easy if the structures of interest were uniformly stained. In choosing labeling methods, try to seek out fluorescent / chromogenic stains that fill the structure of interest as uniformly as possible. For example, some nuclear stains bring out the chromatin texture - this could be confounding to automated nuclear segmentation algorithms. |
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| + | ='''Inadequate Axial Resolution:'''= | ||
| + | Keep in mind that the axial resolution <math> \Delta z</math>of confocal and multi-photon microscopes is invariably poorer than their lateral resolution. When you want to make three-dimensional (3D) measurements of structures, it | ||
Revision as of 14:33, 30 June 2009
Contents |
General Comments
Successful application of computational image analysis tools like FARSIGHT to cell and tissue images benefits from careful specimen preparation and imaging. The purpose of this page is to describe some of the practical issues that would be helpful to biologists and microscopists. Our emphasis is on 3D, multi-channel, and time-lapse microscopy.
In designing the protocols for labeling and imaging specimens, it is helpful to understand some of the major sources of errors in image analysis, and work to minimize them. The following paragraphs describe some of these issues:
Variations in staining:
The hardest first step in computational image analysis is segmentation - the delineation of structures in images. This task would be very easy if the structures of interest were uniformly stained. In choosing labeling methods, try to seek out fluorescent / chromogenic stains that fill the structure of interest as uniformly as possible. For example, some nuclear stains bring out the chromatin texture - this could be confounding to automated nuclear segmentation algorithms.
Inadequate Axial Resolution:
Keep in mind that the axial resolution Δzof confocal and multi-photon microscopes is invariably poorer than their lateral resolution. When you want to make three-dimensional (3D) measurements of structures, it
Protocol for In situ Imaging of the Mouse Thymus Using 2-Photon Microscopy
Ena Ladi, Paul Herzmark, Ellen Robey
Department of Molecular and Cell Biology, University of California, Berkeley
Textual descriptions of these protocols can be found in the papers below.
VIDEO PUBLICATION
This is a video-recorded description of the procedure for recording the 5D movies referred to on this wiki page Tracking.
Journal of Visualized Experiments (2008)
http://www.jove.com/index/details.stp?ID=652
PAPER PUBLICATIONS
[1] Ena Ladi, Tanja Schwickert, Tatyana Chtanova, Ying Chen, Paul Herzmark, Xinye Yin, Holly Aaron, Shiao Wei Chan, Martin Lipp, Badrinath Roysam and Ellen A. Robey, “Thymocyte-dendritic cell interactions near sources of CCR7 ligands in the thymic cortex,” Journal of Immunology 181(10):7014-23, 2008.
[2] Ying Chen, Ena Ladi, Paul Herzmark, Ellen Robey, and Badrinath Roysam, “Automated 5-D Analysis of Cell Migration and Interaction in the Thymic Cortex from Time-Lapse Sequences of 3-D Multi-channel Multi-photon Images” , Journal of Immunological Methods, 340(1):65-80, 2009.
