This book first gives an overview of the applications of Graphics Processing Unit (GPU) for radiation therapy issues. Basic concepts in GPU programming are discussed, together with its advantages and limitations. The second and third parts of the book present GPU applications in a variety of imaging-related issues and therapy-related problems in radiotherapy. The last part discusses potential advanced clinical applications supported by GPU technology. Readers benefit from an in-depth review of GPU-based high-performance computing in radiation therapy.
- Covers all active research topics in GPU in radiotherapy and medical imaging
- Presents current status of GPU applications the radiation therapy field
- Analyzes potential problems of GPU in each specific application and offers potential solutions
Table of Contents
Introduction. Overview of GPU and its Applications in Radiation Therapy. Imaging-Related Problems. Analytic Cone Beam CT Reconstruction. Digitally Reconstructed Radiograph. Iterative Cone Beam CT Reconstruction. Multi-GPU CBCT Reconstruction. 4D-CT and 4D-CBCT Reconstruction Using Temporal Regularizations. PET Reconstruction. Single Modality Rigid and Deformable Registration. Inter-Modality Deformable Registration. CT-CBCT Deformable Registration with Intensity Correction. Tumor Tracking and Real Time Volumetric Imaging via One CBCT Projection. CT Dose Calculations and X-Ray Projection Image Simulations Using MC Method. Noise Reduction of CBCT Projections. Therapy-Related Problems. Superposition/Convolution Dose Calculation. Finite Size Pencil Beam Dose Calculation. Proton Pencil Beam Dose Calculation. Photon Monte Carlo Dose Calculation. Proton Monte Carlo Dose Calculation. Proton Monte Carlo Dose Calculation with Track Repeating Method. IMRT Optimization. VMAT Optimization. Gamma Index Calculations. Non-Voxel Broad-Beam Framework for Treatment Plan Optimization. Other Applications. SCORE System for Online Radiotherapy. Patient-Specific QA System.
Xun Jia, Ph.D., DABR, received his PhD in physics from the University of California Los Angeles in 2009. After his postdoctoral training at University of California San Diego, he joined the faculty team at the Department of Radiation Medicine and Applied Sciences, UCSD in 2011. At UCSD, he developed a number of GPU-based applications to accelerate computationally challenging problems in radiation therapy, including compressed sensing-based low-dose cone beam CT reconstruction and Monte Carlo-based radiation dose calculations. He has coauthored 50 papers published in top peer-reviewed journals in the medical physics field. He is also an active manuscript reviewer for many journals and conferences and is currently serving as a Section Editor for the Journal of Applied Clinical Medical Physics.
Steve B. Jiang, Ph.D., DABR, received his PhD in medical physics from the Medical College of Ohio, and his postdoctoral training at Stanford University. He is currently a professor and the Chief of Division of Medical Physics and Engineering at the Department of Radiation Oncology, University of Texas Southwestern (UTSW) Medical Center. Prior to joining UTSW, he was a tenured professor and the Director of Division of Technology Research at the Department of Radiation Medicine and Applied Sciences, UCSD, and served as Executive Director of the Center for Advanced Radiotherapy Technologies, UCSD. Dr. Jiang pioneered the development of high-performance GPU applications for adaptive radiation therapy. He has published over 110 manuscripts in medical physics journals and over 10 book chapters/review articles. Dr. Jiang served as an Associate Editor for Medical Physics, and as a member of the Editorial Board of Physics in Medicine and Biology. He is also a fellow of American Association of Physicists in Medicine.