Image reconstruction by Mumford-Shah regularization for low-dose CT with multi-GPU acceleration.

Image reconstruction by Mumford-Shah regularization for low-dose CT with multi-GPU acceleration.
Phys Med Biol. 2019 Jun 26;:
Authors: Zhu Y, Wang Q, Li M, Jiang M, Zhang P
Abstract
Mumford-Shah (MS) functional has emerged as a regularization technique in X-ray computed tomography (CT) recently. However, for high-resolution CT applications, the huge size of both projection data and image leads to an implementation difficulty. In this work, we propose an approach to implement and accelerate MS regularization on a multi-GPU platform to resolve the issue of data size and rich onboard memory and computing units. We have established a novel partition scheme of the 3D volume under reconstruction and corresponding multithread parallel acceleration strategy to fully utilize the computing resource of multi-GPUs. Our implementation is highly modularized and can be easily scaled with the configuration of GPUs. Experiment results with simulation data as well as real data demonstrate a superior reconstruction quality in contrast to the total variation regularization approach, especially for the ultra-low-dose case. Moreover, this is the first time that MS regularization is used for 3D reconstruction of huge images up to $3072^3$ voxels within 12 minutes.
PMID: 31239414 [PubMed - as supplied by publisher]

Source: Physics in Medicine and Biology - June 25, 2019 Category: Physics Authors: Zhu Y, Wang Q, Li M, Jiang M, Zhang P Tags: Phys Med Biol Source Type: research