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SPECT-MPI iterative denoising during the reconstruction process using a two-phase learned convolutional neural network

Autor: Farnaz Yousefzadeh, Mehran Yazdi, Seyed Mohammad Entezarmahdi, Reza Faghihi, Sadegh Ghasempoor, Negar Shahamiri, Zahra Abuee Mehrizi, Mahdi Haghighatafshar

Publikováno v: EJNMMI Physics, Vol 11, Iss 1, Pp 1-22 (2024)

Abstract Purpose The problem of image denoising in single-photon emission computed tomography (SPECT) myocardial perfusion imaging (MPI) is a fundamental challenge. Although various image processing techniques have been presented, they may degrade th

Externí odkaz: https://doaj.org/article/1a2f20db14744eb1ae7bc34e8aee9538

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Akademický článek

SPECT-MPI iterative denoising during the reconstruction process using a two-phase learned convolutional neural network.

Autor: Yousefzadeh, Farnaz¹ (AUTHOR), Yazdi, Mehran² (AUTHOR) yazdi@shirazu.ac.ir, Entezarmahdi, Seyed Mohammad³ (AUTHOR), Faghihi, Reza⁴ (AUTHOR), Ghasempoor, Sadegh⁵ (AUTHOR), Shahamiri, Negar (AUTHOR), Mehrizi, Zahra Abuee³ (AUTHOR), Haghighatafshar, Mahdi³ (AUTHOR)

Publikováno v: EJNMMI Physics. 10/8/2024, Vol. 11 Issue 1, p1-22. 22p.

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Point cloud-based registration and image fusion between cardiac SPECT MPI and CTA

Autor: Tang, Shaojie, Miao, Penpen, Gao, Xingyu, Zhong, Yu, Zhu, Dantong, Wen, Haixing, Xu, Zhihui, Wei, Qiuyue, Yao, Hongping, Huang, Xin, Gao, Rui, Zhao, Chen, Zhou, Weihua

A method was proposed for the point cloud-based registration and image fusion between cardiac single photon emission computed tomography (SPECT) myocardial perfusion images (MPI) and cardiac computed tomography angiograms (CTA). Firstly, the left ven

Externí odkaz: http://arxiv.org/abs/2402.06841

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Akademický článek

Real-world evidence study on the impact of SPECT MPI, PET MPI, cCTA and stress echocardiography on downstream healthcare utilisation in patients with coronary artery disease in the US

Autor: Matthieu Pelletier-Galarneau, Arturo Cabra, Erika Szabo, Santosh Angadageri

Publikováno v: BMC Cardiovascular Disorders, Vol 24, Iss 1, Pp 1-12 (2024)

Abstract Background Coronary artery disease (CAD) is associated with a large clinical and economic burden. However, consensus on the optimal approach to CAD diagnosis is lacking. This study sought to compare downstream healthcare resource utilisation

Externí odkaz: https://doaj.org/article/f025a5cb044547f3812b9aef62d6259a

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Classification of coronary artery disease severity based on SPECT MPI polarmap images and deep learning: A study on multi-vessel disease prediction

Autor: Jui-Jen Chen, Ting-Yi Su, Chien-Che Huang, Ta-Hsin Yang, Yen-Hsiang Chang, Henry Horng-Shing Lu

Publikováno v: Digital Health, Vol 10 (2024)

Background Coronary artery disease (CAD) is a global health concern. Conventional single photon emission computed tomography myocardial perfusion imaging (SPECT MPI) is a noninvasive method for assessing the severity of CAD. However, it relies on man

Externí odkaz: https://doaj.org/article/5f0d86ea9dc642419472befa73a27786

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A new method using machine learning to integrate ECG and gated SPECT MPI for Cardiac Resynchronization Therapy Decision Support on behalf of the VISION-CRT

Autor: Fernandes, Fernando de A., Larsen, Kristoffer, He, Zhuo, Nascimento, Erivelton, Peix, Amalia, Sha, Qiuying, Paez, Diana, Garcia, Ernest V., Zhou, Weihua, Mesquita, Claudio T

Cardiac resynchronization therapy (CRT) has been established as an important therapy for heart failure. Mechanical dyssynchrony has the potential to predict responders to CRT. The aim of this study was to report the development and the validation of

Externí odkaz: http://arxiv.org/abs/2211.07472

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