A review of state-of-the-art resolution improvement techniques in SPECT imaging
Abstract Single photon emission computed tomography (SPECT), a technique capable of capturing functional and molecular information, has been widely adopted in theranostics applications across various fields, including cardiology, neurology, and oncology. The spatial resolution of SPECT imaging is re...
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2025-01-01
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Online Access: | https://doi.org/10.1186/s40658-025-00724-9 |
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author | Zhibiao Cheng Ping Chen Jianhua Yan |
author_facet | Zhibiao Cheng Ping Chen Jianhua Yan |
author_sort | Zhibiao Cheng |
collection | DOAJ |
description | Abstract Single photon emission computed tomography (SPECT), a technique capable of capturing functional and molecular information, has been widely adopted in theranostics applications across various fields, including cardiology, neurology, and oncology. The spatial resolution of SPECT imaging is relatively poor, which poses a significant limitation, especially the visualization of small lesions. The main factors affecting the limited spatial resolution of SPECT include projection sampling techniques, hardware and software. Both hardware and software innovations have contributed substantially to improved SPECT imaging quality. The present review provides an overview of state-of-the-art methods for improving spatial resolution in clinical and pre-clinical SPECT systems. It delves into advancements in detector design and modifications, projection sampling techniques, traditional reconstruction algorithm development and optimization, and the emerging role of deep learning. Hardware enhancements can result in SPECT systems that are both lighter and more compact, while also improving spatial resolution. Software innovations can mitigate the costs of hardware modifications. This survey offers a thorough overview of the rapid advancements in resolution enhancement techniques within the field of SPECT, with the objective of identifying the most recent trends. This is anticipated to facilitate further optimization and improvement of clinical systems, enabling the visualization of small lesions in the early stages of tumor detection, thereby enhancing accurate localization and facilitating both diagnostic imaging and radionuclide therapy, ultimately benefiting both clinicians and patients. |
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institution | Kabale University |
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language | English |
publishDate | 2025-01-01 |
publisher | SpringerOpen |
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series | EJNMMI Physics |
spelling | doaj-art-463adbd7be064ea9a3728f5ffe62d7512025-02-02T12:43:10ZengSpringerOpenEJNMMI Physics2197-73642025-01-0112112310.1186/s40658-025-00724-9A review of state-of-the-art resolution improvement techniques in SPECT imagingZhibiao Cheng0Ping Chen1Jianhua Yan2School of Information and Communication Engineering, North University of ChinaSchool of Information and Communication Engineering, North University of ChinaDepartment of Nuclear Medicine, Division of Life Sciences and Medicine, The First Affiliated Hospital of USTC, University of Science and Technology of ChinaAbstract Single photon emission computed tomography (SPECT), a technique capable of capturing functional and molecular information, has been widely adopted in theranostics applications across various fields, including cardiology, neurology, and oncology. The spatial resolution of SPECT imaging is relatively poor, which poses a significant limitation, especially the visualization of small lesions. The main factors affecting the limited spatial resolution of SPECT include projection sampling techniques, hardware and software. Both hardware and software innovations have contributed substantially to improved SPECT imaging quality. The present review provides an overview of state-of-the-art methods for improving spatial resolution in clinical and pre-clinical SPECT systems. It delves into advancements in detector design and modifications, projection sampling techniques, traditional reconstruction algorithm development and optimization, and the emerging role of deep learning. Hardware enhancements can result in SPECT systems that are both lighter and more compact, while also improving spatial resolution. Software innovations can mitigate the costs of hardware modifications. This survey offers a thorough overview of the rapid advancements in resolution enhancement techniques within the field of SPECT, with the objective of identifying the most recent trends. This is anticipated to facilitate further optimization and improvement of clinical systems, enabling the visualization of small lesions in the early stages of tumor detection, thereby enhancing accurate localization and facilitating both diagnostic imaging and radionuclide therapy, ultimately benefiting both clinicians and patients.https://doi.org/10.1186/s40658-025-00724-9SPECT systemResolution improvementHardwareSoftwareDeep learning |
spellingShingle | Zhibiao Cheng Ping Chen Jianhua Yan A review of state-of-the-art resolution improvement techniques in SPECT imaging EJNMMI Physics SPECT system Resolution improvement Hardware Software Deep learning |
title | A review of state-of-the-art resolution improvement techniques in SPECT imaging |
title_full | A review of state-of-the-art resolution improvement techniques in SPECT imaging |
title_fullStr | A review of state-of-the-art resolution improvement techniques in SPECT imaging |
title_full_unstemmed | A review of state-of-the-art resolution improvement techniques in SPECT imaging |
title_short | A review of state-of-the-art resolution improvement techniques in SPECT imaging |
title_sort | review of state of the art resolution improvement techniques in spect imaging |
topic | SPECT system Resolution improvement Hardware Software Deep learning |
url | https://doi.org/10.1186/s40658-025-00724-9 |
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