Fast, Accurate and Shift-Varying Line Projections for Iterative Reconstruction Using the GPU

By Guillem Pratx, Garry Chinn, Peter D. Olcott, Craig S. Levin. 2009

115 citations recorded by the source corpus.

List-mode processing provides an efficient way to deal with sparse projections in iterative image reconstruction for emission tomography. An issue often reported is the tremendous amount of computation required by such algorithm. Each recorded event requires several back- and forward line projections. We investigated the use of the programmable graphics processing unit (GPU) to accelerate the line-projection operations and implement fully-3D list-mode ordered-subsets expectation-maximization for positron emission tomography (PET). We designed a reconstruction approach that incorporates resolution kernels, which model the spatially-varying physical processes associated with photon emission, transport and detection. Our development is particularly suitable for applications where the projection data is sparse, such as high-resolution, dynamic, and time-of-flight PET reconstruction. The GPU approach runs more than 50 times faster than an equivalent CPU implementation while image quality and accuracy are virtually identical. This paper describes in details how the GPU can be used to accelerate the line projection operations, even when the lines-of-response have arbitrary endpoint locations and shift-varying resolution kernels are used. A quantitative evaluation is included to validate the correctness of this new approach.

Subfields: Radiation, Radiology, Nuclear Medicine and Imaging

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Citations in the corpus

Maximum-Likelihood Estimation With a Contracting-Grid Search Algorithm (2010, background): “Consequently, many research projects now use GPU hardware [29]–[34].”
Medical image processing on the GPU - Past, present and future (2013, background): “Pratx et al. (2009) focused on reconstruction of sparse projection data stored in list-mode format, commonly used for high-resolution, dynamic and timeof-flight (ToF) PET.”
GPU computing in medical physics: a review. (2011, methodology): “The ﬁrst implementation of list-mode reconstruction was developed for the GPU 28 using the graphics pipeline.”