Skip to Main Content
It is well known that the human genome has multiscale structures; multiscale approaches at the cellular, molecular, and sequence levels have been used to detect genomic variations, which are associated with phenotypic differences or diseases including cancers. Reaping the fruit of human genome sequencing, high-resolution imaging probes have been designed in recent years. Combined with image processing techniques, they enable the detection of cryptic and complex genetic aberrations at higher resolutions, holding great promise for personalized medicine. However, fulfilling the promise calls for powerful analytic techniques to handle the vast amount of imaging data generated by these high resolution imaging probes. Signal processing techniques such as wavelets play an important role in addressing computational challenges in this emerging area.
Date of Publication: November 2009