Deep learning approach using SPECT-to-PET translation for attenuation correction in CT-less myocardial perfusion SPECT imaging

被引:0
作者
Masateru Kawakubo
Michinobu Nagao
Yoko Kaimoto
Risako Nakao
Atsushi Yamamoto
Hiroshi Kawasaki
Takafumi Iwaguchi
Yuka Matsuo
Koichiro Kaneko
Akiko Sakai
Shuji Sakai
机构
[1] Kyushu University,Department of Health Sciences, Faculty of Medical Sciences
[2] Tokyo Women’s Medical University,Department of Diagnostic Imaging and Nuclear Medicine
[3] Tokyo Women’s Medical University,Department of Radiology
[4] Tokyo Women’s Medical University,Department of Cardiology
[5] Kyushu University,Department of Advanced Information Technology, Faculty of Information Science and Electrical Engineering
来源
Annals of Nuclear Medicine | 2024年 / 38卷
关键词
N ammonia PET; Cardiac SPECT; Myocardial perfusion imaging; Attenuation correction; Deep learning;
D O I
暂无
中图分类号
学科分类号
摘要
引用
收藏
页码:199 / 209
页数:10
相关论文
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[1]  
Dorbala S(2018)Single photon emission computed tomography (SPECT) myocardial perfusion imaging guidelines: instrumentation, acquisition, processing, and interpretation J Nucl Cardiol 25 1784-1846
[2]  
Ananthasubramaniam K(2005)Attenuation correction single-photon emission computed tomography myocardial perfusion imaging Semin Nucl Med 35 37-51
[3]  
Armstrong IS(2019)State-of-the-art deep learning in cardiovascular image analysis JACC Cardiovasc Imaging 12 1549-1565
[4]  
Chareonthaitawee P(2022)Artificial intelligence-based attenuation correction; closer to clinical reality? J Nucl Cardiol 29 2251-2253
[5]  
DePuey EG(2020)Deep learning-based attenuation map generation for myocardial perfusion SPECT Eur J Nucl Med Mol Imaging 47 2383-2395
[6]  
Einstein AJ(2022)Post-reconstruction attenuation correction for SPECT myocardium perfusion imaging facilitated by deep learning-based attenuation map generation J Nucl Cardiol 29 2881-2892
[7]  
Bateman TM(2021)Direct attenuation correction using deep learning for cardiac SPECT: a feasibility study J Nucl Med 62 1645-1652
[8]  
Cullom SJ(2023)DuDoSS: deep-learning-based dual-domain sinogram synthesis from sparsely sampled projections of cardiac SPECT Med Phys 50 89-103
[9]  
Litjens G(2022)‘Virtual’ attenuation correction: improving stress myocardial perfusion SPECT imaging using deep learning Eur J Nucl Med Mol Imaging 49 3140-3149
[10]  
Ciompi F(2005)Attenuation correction of myocardial SPECT perfusion images with low-dose CT: evaluation of the method by comparison with perfusion PET J Nucl Med 46 736-744