- Top of page
- SPECTRAL IMAGING
- REALIZATION OF SPECTRAL IMAGES
- SPECTRAL IMAGING CHALLENGE: INFORMATION VERSUS TIME
- SPECTRAL IMAGE PROCESSING
- LINEAR DECOMPOSITION (FLUORESCENCE)
- SIMILARITY MAPPING
- SPECTRAL UNMIXING FOR TRANSMISSION (BRIGHT FIELD) MEASUREMENTS
- NONSUPERVISED METHODS AND PRINCIPLE COMPONENTS ANALYSIS
- DISCUSSION AND CONCLUSIONS
- LITERATURE CITED
Spectral imaging extends the capabilities of biological and clinical studies to simultaneously study multiple features such as organelles and proteins qualitatively and quantitatively. Spectral imaging combines two well-known scientific methodologies, namely spectroscopy and imaging, to provide a new advantageous tool. The need to measure the spectrum at each point of the image requires combining dispersive optics with the more common imaging equipment, and introduces constrains as well.
Methods and Results:
The principles of spectral imaging and a few representative applications are described. Spectral imaging analysis is necessary because the complex data structure cannot be analyzed visually. A few of the algorithms are discussed with emphasis on the usage for different experimental modes (fluorescence and bright field). Finally, spectral imaging, like any method, should be evaluated in light of its advantages to specific applications, a selection of which is described.
Spectral imaging is a relatively new technique and its full potential is yet to be exploited. Nevertheless, several applications have already shown its potential. © 2006 International Society for Analytical Cytology