GPU-Accelerated Parallel Gene-pool Optimal Mixing Applied to Multi-Objective Deformable Image Registration

IEEE Congress on Evolutionary Computation (CEC)

Abstract

The Real-Valued Gene-pool Optimal Mixing Evolutionary Algorithm (RV-GOMEA) has previously been successfully used to achieve highly scalable optimization of various real-world problems in a gray-box optimization setting. Deformable Image Registration (DIR) is a multi-objective problem, aimed at finding the most likely non-rigid deformation of a given source image so that it matches a given target image. We specifically consider the case where the deformation model allows for finite-element-type modeling of tissue properties. This optimization problem is non-smooth, necessitating techniques like EAs to get good results. Though the objectives of DIR are non-separable, non-neighboring regions of the deformation grid are conditionally independent. We show that GOMEA allows to exploit such knowledge through the large-scale parallel application of variation steps, where each is only accepted when leading to an improvement, on a Graphics Processing Unit (GPU). On various 2-dimensional DIR problems, we find that this way, similar results can be achieved as when sequential processing is performed, while allowing for substantial speed-ups (up to a factor of 111) for the highest-dimensional problems (i.e., the highest deformation-grid resolution). This work opens the door to the extension of this type of DIR to larger (3-dimensional) deformation grids, and its application to other real-world problems.

Authors 3

1. Anton Bouter

   Centrum Wiskunde & Informatica

   Affiliation as printed

   Centrum Wiskunde & Informatica,Life Sciences and Health Group,Amsterdam,The Netherlands

2. Tanja Alderliesten Aachen Department of Radiation Oncology

   Leiden University Medical Center

   Affiliation as printed

   Leiden University Medical Center,Department of Radiation Oncology,Leiden,The Netherlands

3. Peter A. N. Bosman

   Delft University of Technology · Centrum Wiskunde & Informatica

   Affiliation as printed

   Centrum Wiskunde & Informatica,Life Sciences and Health Group,Amsterdam,The Netherlands

   Delft University of Technology, Delft, The Netherlands