Performance optimization of block matching in 3D echocardiography

Abstract

The introduction of real time 3D echocardiography allows for deformation tracking in three dimensions, without the limitations of 2D methods. However, the processing needs of 3D methods are much higher. The aim of the study was to optimize the performance of 3D block matching by using a Single Instruction Multiple Data (SIMD) model, a technique employed to achieve data level parallelism. Two implementations of SIMD have been tested. The first is based on Streaming SIMD Extensions (SSE), the second uses CUDA, a SIMD architecture proposed by NVIDIA, which is available on several graphics cards. The proposed methods have been validated on synthetic and patient data. With the use of SIMD architecture, the overall processing time is significantly reduced, thus making 3D speckle tracking feasible in a clinical setting. Apart from the implemented sum of square differences (SAD), other matching criteria (e.g. sum of squared differences, normalized cross correlation) can be implemented efficiently (especially on the GPU) thus further improving the accuracy of the block matching process.