Abstract
Due to the increase in the size of medical images, huge computational complexity is required for image analysis and feature extraction. In order to address this problem, parallelization of processing has become increasingly important in recent years. The Message Passing Interface (MPI) is a common library for developing parallel programs. High-speed processing can be realized using MPI, but it is necessary for programmers to consider how to split the data and how to process the data transmitted and received between CPUs. Programming therefore becomes more complicated. In previous research, a parallel programming interface based on MPI was developed, but the method employed in this previous research can only split simple arrays. In the field of medical imaging, the Insight Segmentation and Registration Toolkit (ITK) is the most commonly used image-processing library worldwide. However, because ITK has a unique data structure, the methods employed in the previous research are not applicable to ITK. The authors have therefore developed a set of macros based on MPI that can be applied to programs using ITK. The authors have also verified the effectiveness of the proposed method based on experimental results.
