Dictionary learning for medical image denoising, reconstruction, and segmentation

Modeling data as sparse linear combinations of basis elements from a learnt dictionary has been widely used in signal processing and machine learning. The learnt dictionary, which is well adapted to specific data, has proven to be very effective in image restoration and classification tasks. In this chapter, we will review the most popular dictionary learning techniques such as K-SVD and online dictionary learning. We will also demonstrate how these techniques can be applied to medical imaging applications including image denoising, reconstruction, super-resolution and segmentation.