Imaging systems extract finer details

While appreciative of the imaging data and results currently available, skilled imaging-equipment users are pushing to obtain even more information, especially for evaluating the finer details of, say, cancerous tumors and scientific specimens. They are asking imaging-system developers to come up with techniques to uncover even more hidden data from images. Until recently, developers were thwarted by limited processor power, storage restrictions, and complex software. However, due to recent adva

Imaging systems extract finer details

George Kotelly Executive Editor

georgek@pennwell.com

While appreciative of the imaging data and results currently available, skilled imaging-equipment users are pushing to obtain even more information, especially for evaluating the finer details of, say, cancerous tumors and scientific specimens. They are asking imaging-system developers to come up with techniques to uncover even more hidden data from images. Until recently, developers were thwarted by limited processor power, storage restrictions, and complex software. However, due to recent advances in hardware and software, machine-vision and imaging systems are detecting, processing, analyzing, and displaying a range of heretofore unavailable details.

By offering a range of imaging scan rates, a confocal-laser-scanning imaging system can capture fine details and fast dynamic events in biological specimens while minimizing exposure to laser light illumination. As described by Dave Wilson, this system detects a single pixel at a time rather than the entire specimen area.

Image-reconstruction techniques are being investigated by machine-vision and imaging researchers to restore the obscured details of degraded images. According to contributing editor Richard Parker, image reconstruction is finding widespread acceptance in medical diagnosis, weather forecasting, radar-signal analysis, and adaptive-optics applications .

In most imaging systems, the massive amounts of digital data generated present storage challenges for system integrators. Of all the available image-compression approaches, claims editor-at-large Andy Wilson, wavelet-based software performs better for handling large data quantities .

An all-digital-imaging system is enabling ophthalmologists to clearly see the back of a patient`s eye and provide images in greater detail than previously available. It integrates two cameras, a 64-bit processor, and custom software, says contributor Michael McMinn, to deliver digital images in less than 1 s and at less cost than film .

To select a CRT color monitor for sharply defined images, system integrators must examine key product specifications and scrutinize diverse technologies, standards, and environmental limitations. As explained by editor-at-large Andy Wilson, choosing products from more than 60 display-monitor vendors translates into a methodical analysis process.

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