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Cited by in F6Publishing
For: Nesterov SV, Lee BC, Moody JB, Slomka P, Han C, Knuuti JM. The Status and Future of PET Myocardial Blood Flow Quantification Software. Annals of Nuclear Cardiology 2016;2:106-110. [DOI: 10.17996/anc.02.01.106] [Cited by in Crossref: 9] [Cited by in F6Publishing: 9] [Article Influence: 1.3] [Reference Citation Analysis]
Number Citing Articles
1 Tankeshwar K, Srivastava S. Role of Microfluidics and Nanofluidics in Managing CAD. Biomedical Translational Research 2022. [DOI: 10.1007/978-981-16-9232-1_16] [Reference Citation Analysis]
2 Nesterov SV, Knuuti JM. 82Rb-PET MPQ: Do normal values exist? J Nucl Cardiol 2020. [PMID: 33000406 DOI: 10.1007/s12350-020-02362-3] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 0.7] [Reference Citation Analysis]
3 Liu H, Wu J, Sun J, Wu T, Fazzone‐chettiar R, Thorn S, Sinusas AJ, Liu Y. A robust segmentation method with triple‐factor non‐negative matrix factorization for myocardial blood flow quantification from dynamic 82 Rb positron emission tomography. Med Phys 2019;46:5002-5013. [DOI: 10.1002/mp.13783] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 0.5] [Reference Citation Analysis]
4 Sun J, Wu T, Liu H, Liu Y. A Novel Three-Dimensional Clustering Method Incorporated with Ellipsoid Model Fitting for Personalizing Myocardial Perfusion Positron Emission Tomography Image Segmentation. 2018 IEEE Nuclear Science Symposium and Medical Imaging Conference Proceedings (NSS/MIC) 2018. [DOI: 10.1109/nssmic.2018.8824346] [Reference Citation Analysis]
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