Utilizing Hierarchical Multiprocessing for Medical Image Registration

Abstract

dvances in medical imaging technologies have enabled medical diagnoses and procedures that were simply not possible a decade ago. The accelerating speed of acquisition and the increasing resolution of images have given doctors more information, which is taken less invasively about their patients. However, because of the multitude of imaging modalities [e.g., computed tomography (CT), positron emission tomography (PET), magnetic resonance imaging (MRI), and ultrasound (US)] and the sheer volume of data being acquired, utilizing this new data effectively has become problematic. One way to tap into the potential of this raw data is to merge these images into one integrated view through a procedure called image registration. COMPUTE-ENABLED MEDICINEFor the past decade, improving performance and accuracy has been a driving force of innovation in automated medical image registration. The ultimate goal of accurate, robust, real-time image registration will enhance diagnoses of patients and enable new image-guided intervention techniques. With such a computationally intensive and multifaceted problem, improvements have been found in high-performance platforms such as graphics processing units (GPUs) and general-purpose multicore systems, but there has yet to be a solution fast enough and effective enough to gain widespread clinical use.

Dataflow-Based Design and Implementation of Image Processing Applications

“…For example, GPUs are used extensively in computer vision, where computationally intensive kernels require acceleration to work in real time or on video streams [27]. Medical images may be enhanced through a variety of image processing techniques, and the GPU is leading to computationally intensive processing techniques that are clinically viable [28].…”

Novel and robust methods for the automatic registration of image data

“…-CPU [151] -GPU [117,122,[163][164][165] -Both [5,[166][167][168] • Standalone [5, 151] [163] or Grid [14,28,129,167,[169][170][171][172][173][174][175] • The degree of parallelization:…”