Improving detection accuracy of perfusion defect in standard dose SPECT-myocardial perfusion imaging by deep-learning denoising.

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作者： Junchi,Liu ^[1] ; Yongyi,Yang ^[2] ; Miles N,Wernick ^[1] ; P Hendrik,Pretorius ^[3] ; Piotr J,Slomka ^[4] ; Michael A,King ^[3]

作者单位： Medical Imaging Research Center and Department of Electrical and Computer Engineering, Illinois Institute of Technology, Chicago, IL, 60616, USA. ^[1] Medical Imaging Research Center and Department of Electrical and Computer Engineering, Illinois Institute of Technology, Chicago, IL, 60616, USA. yangyo@iit.edu. ^[2] Department of Radiology, University of Massachusetts Medical School, Worcester, MA, USA. ^[3] Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA, USA. ^[4]

关键词 SPECT-MPI deep learning noise-to-noise training post-reconstruction filtering

主题词人类(Humans);图像处理, 计算机辅助(Image Processing, Computer-Assisted);心肌灌注显像(Myocardial Perfusion Imaging);灌流(Perfusion);ROC曲线(ROC Curve);体层摄影术, 发射型计算机, 单光子(Tomography, Emission-Computed, Single-Photon)

DOI 10.1007/s12350-021-02676-w

PMID 34282538

发布时间 2024-01-30

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