Development of Fast Reconstruction Techniques for Prompt Gamma Imaging during Proton Radiotherapy
| dc.contributor.author | Casilag, Johnlemuel | |
| dc.contributor.author | Della-Giustina, James | |
| dc.contributor.author | Gregorio, Elizabeth | |
| dc.contributor.author | Jacob, Aniebiet | |
| dc.contributor.author | Barajas, Carlos A. | |
| dc.contributor.author | Gobbert, Matthias | |
| dc.contributor.author | Mackin, Dennis S. | |
| dc.contributor.author | Polf, Jerimy | |
| dc.date.accessioned | 2025-08-13T20:14:33Z | |
| dc.date.issued | 2017 | |
| dc.description.abstract | Proton beam radiation treatment was first proposed by Robert Wilson in 1946. The advantage of proton beam radiation is that the lethal dose of radiation is delivered by a sharp increase toward the end of the beam range. This sharp increase, known as the Bragg peak, allows for the possibility of reducing the exposure of healthy tissue to radiation when comparing to x-ray radiation treatment. As the proton beam interacts with the molecules in the body, gamma rays are emitted. The origin of the gamma rays gives the location of the proton beam in the body, therefore, gamma ray imaging allows physicians to better take advantage of the benefits of proton beam radiation. These gamma rays are detected using a Compton Camera (CC) while the SOE algorithm is used to reconstruct images of these gamma rays as they are emitted from the patient. This imaging occurs while the radiation dose is delivered, which would allow the physician to make adjustments in real time in the treatment room, provided the image reconstruction is computed fast enough. This project focuses on speeding up the image reconstruction software with the use of of parallel computing techniques involving MPI. Additionally, we demonstrate the use of the VTune performance analyzer to identify bottlenecks in a parallel code. | |
| dc.description.sponsorship | These results were obtained as part of the REU Site: Interdisciplinary Program in High Performance Computing (hpcreu.umbc.edu) in the Department of Mathematics and Statistics at the University of Maryland, Baltimore County (UMBC) in Summer 2017. This program is funded by the National Science Foundation (NSF), the National Security Agency (NSA), and the Department of Defense (DOD), with additional support from UMBC, the Department of Mathematics and Statistics, the Center for Interdisciplinary Research and Consulting (CIRC), and the UMBC High Performance Computing Facility (HPCF). HPCF is supported by the U.S. National Science Foundation through the MRI program (grant nos. CNS–0821258 and CNS–1228778) and the SCREMS program (grant no. DMS–0821311), with additional substantial support from UMBC. Co-author James Della-Giustina was supported in part, by the Math Computer Inspired Scholars program, through funding from the National Science Foundation and also the Constellation STEM Scholars Program, funded by Constellation Energy. Co-authors Johnlemuel Casilag and Aniebiet Jacob were supported, in part, by the UMBC National Security Agency (NSA) Scholars Program through a contract with the NSA. Graduate assistant Carlos Barajas was supported by UMBC. We acknowledge the Texas Advanced Computing Center (TACC) at The University of Texas at Austin for providing HPC resources that have contributed to the research results reported within this paper. | |
| dc.description.uri | https://hpcf-files.umbc.edu/research/papers/REU2017Team6.pdf | |
| dc.format.extent | 26 pages | |
| dc.genre | technical reports | |
| dc.genre | preprints | |
| dc.identifier | doi:10.13016/m2owhv-blal | |
| dc.identifier.uri | http://hdl.handle.net/11603/39782 | |
| dc.language.iso | en | |
| dc.relation.isAvailableAt | The University of Maryland, Baltimore County (UMBC) | |
| dc.relation.ispartof | UMBC Mathematics and Statistics Department | |
| dc.relation.ispartof | UMBC Faculty Collection | |
| dc.relation.ispartof | UMBC Student Collection | |
| dc.relation.ispartof | UMBC Computer Science and Electrical Engineering Department | |
| dc.relation.ispartof | UMBC Imaging Research Center (IRC) | |
| dc.rights | This item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author. | |
| dc.subject | UMBC Behavior and Information in Medicine Lab | |
| dc.subject | UMBC High Performance Computing Facility (HPCF) | |
| dc.title | Development of Fast Reconstruction Techniques for Prompt Gamma Imaging during Proton Radiotherapy | |
| dc.type | Text | |
| dcterms.creator | https://orcid.org/0000-0003-1745-2292 |
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