The clarity of signals in systems such as radar, sonar and even radiography could give much more clarity in detection of breast cancer by using stochastic resonance (SR), which are used in medical clinics to detect signs of breast cancer, according to a Syracuse University research team.
The study distinctly improved the system's ability to correctly identify precancerous lesions, plus a 36 percent reduction in false positives.
The inventors have developed a novel method of calculating precisely the correct type and level of noise to add to existing noise in radiography or a similar system.
"We see a broad spectrum of applications for this technology. If a system's performance is unsatisfactory, we add noise to the system based on a specific algorithm that can significantly improve system performance," said research assistant professor Hao Chen.
While the current focus of the research group is on medical uses of stochastic resonance, other applications are expected in enhancing audio, video, geophysical, environmental, radar and other signals.
Ongoing investigations by the Syracuse group are expected to produce further improvements in the efficiency and robustness of the SR-based detection techniques.
A paper by the inventors on theory of stochastic resonance stochastic resonance effect in signal detection was published in Signal Processing in July 2007.