Automated image analysis technologies for biological 3D light microscopy
✍ Scribed by James N. Turner; Hakan Ancin; Douglas E. Becker; D. H. Szarowski; Maria Holmes; Nate O'Connor; Michael Wang; Timothy Holmes; Badrinath Roysam
- Publisher
- John Wiley and Sons
- Year
- 1997
- Tongue
- English
- Weight
- 603 KB
- Volume
- 8
- Category
- Article
- ISSN
- 0899-9457
No coin nor oath required. For personal study only.
✦ Synopsis
Techniques for three-dimensional (3D) light microsocpy throughout the volume of the specimen, not just a stereo image.
of a wide variety of biological specimens are rapidly maturing. The Three-dimensional imaging is especially valuable when the specinext advances are to improve image contrast, make image resolution men is substantially thicker than the depth of field of the microas isotropic as possible, and perform quantitative analysis. This article scope, which is the case for the vast majority of biological specidiscusses methods of automatic image analysis and blind deconvolumens. Even single cultured cells are usually thicker than the tion to compensate for the microscope's point-spread function (immicroscope's depth of field when using an objective lens with a pulse response). Special emphasis is given to quantitative analysis high numerical aperture. The technique provides more detailed based on adaptive segmentation, the results of which can be used and more faithful visualization of specimens than conventional to quantify and trace individual structures, and to montage high-resolution fields as well as the results of image analysis on these fields 2D methods or 3D methods based on serial physical sectioning into a wide-area view with an associated computer database repre- [1][2][3][4]. For instance, the confocal laser-scanned microscope sentation. We exploit the specific advantages accruing from the 3D (CLSM) has been used to produce detailed 3D visualizations of nature of the data to achieve new capabilities not possible with 2D thick tissues and cells in culture [4 -6]. We used a CLSM to imaging. Fundamental and practical challenges in this area and our correlate the 3D structure and electrophysiology of selectively progress to date including automated segmentation, cell counting, stained neurons in intact brain tissue [5,[8][9][10][11][12][13][14].
neuron tracing, mosaic synthesis, ''blind'' deconvolution of large 3D All 3D light microscopy is based on optical sectioning, i.e., images, and high-speed computation are presented.