New applications of super-resolution in medical imaging
The image processing algorithms collectively known as super-resolution have proven effective in producing high-quality imagery from a collection of low-resolution photographic images. In this chapter, we examine some of the advantages and challenges of applying the super-resolution framework to applications in medical imaging. We describe two novel applications in detail. The first application addresses the problem of improving the quality of digital mammography imaging systems while reducing X-ray radiation exposure. The second application addresses the problem of improving the spatiotemporal resolution of spectral domain optical coherence tomography systems in the presence of uncontrollable patient motion. Experimental results on real data sets confirm the effectiveness of the proposed methodologies.
