Key points are not available for this paper at this time.
In this article, we look at early, recent, and state-of-the-art methods for registration of medical images using a range of high-performance computing (HPC) architectures including symmetric multiprocessing (SMP), massively multiprocessing (MMP), and architectures with distributed memory (DM), and nonuniform memory access (NUMA). The article is designed to be self-sufficient. We will take the time to define and describe concepts of interest, albeit briefly, in the context of image registration and HPC. We provide an overview of the registration problem and its main components in the section "Registration." Our main focus will be HPC-related aspects, and we will highlight relevant issues as we explore the problem domain. This approach presents a fresh angle on the subject than previously investigated by the more general and classic reviews in the literature 1-3. The sections "Multi-CPU Implementations" and "Accelerator Implementations" are organized from the perspective of high-performance and parallel- computing with the registration problem embodied. This is meant to equip the reader with the knowledge to map a registration problem to a given computing architecture.
Shams et al. (Mon,) studied this question.