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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Main Authors: Zhibiao Cheng, Ping Chen, Jianhua Yan
Format: Article
Language:English
Published: SpringerOpen 2025-01-01
Series:EJNMMI Physics
Subjects:
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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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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