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Atherosclerosis|July 7, 2012
Coronary microvascular dysfunction is associated with higher frequency of thin-cap fibroatheromaSaurabh S Dhawan, Michel T Corban, Ravi A Nanjundappa, et al.Catheterization and Cardiovascular Interventions : Official Journal of the Society for Cardiac Angiography & Interventions|September 14, 2006
Outcome of patients with acute coronary syndromes and moderate coronary lesions undergoing deferral of revascularization based on fractional flow reserve assessmentJoshua J Fischer, Xin-Qun Wang, Habib Samady, et al.The American Journal of Cardiology|July 20, 2002
Comparison between visual assessment and quantitative angiography versus fractional flow reserve for native coronary narrowings of moderate severityJoshua J Fischer, Habib Samady, John A McPherson, et al.Atherosclerosis|June 28, 2011
The role of plasma aminothiols in the prediction of coronary microvascular dysfunction and plaque vulnerabilitySaurabh S Dhawan, Parham Eshtehardi, Michael C McDaniel, et al.IEEE Transactions on Medical Imaging|June 26, 2013
Framework to co-register longitudinal virtual histology-intravascular ultrasound data in the circumferential directionLucas H Timmins, Jonathan D Suever, Parham Eshtehardi, et al.The International Journal of Cardiovascular Imaging|July 9, 2015
Intravascular ultrasound and optical coherence tomography imaging of coronary atherosclerosisCharis Costopoulos, Adam J Brown, Zhongzhao Teng, et al.Cardiovascular Engineering and Technology|November 19, 2015
Co-localization of Disturbed Flow Patterns and Occlusive Cardiac Allograft Vasculopathy Lesion Formation in Heart Transplant PatientsLucas H Timmins, Divya Gupta, Michel T Corban, et al.Journal of the American College of Cardiology|July 10, 2003
Incremental value of combined perfusion and function over perfusion alone by gated SPECT myocardial perfusion imaging for detection of severe three-vessel coronary artery diseaseRonaldo S L Lima, Denny D Watson, Allen R Goode, et al.Biomedical Engineering Online|April 7, 2021
Predicting plaque vulnerability change using intravascular ultrasound + optical coherence tomography image-based fluid-structure interaction models and machine learning methods with patient follow-up data: a feasibility studyXiaoya Guo, Akiko Maehara, Mitsuaki Matsumura, et al.Frontiers in Physiology|May 27, 2022
Predicting Coronary Stenosis Progression Using Plaque Fatigue From IVUS-Based Thin-Slice Models: A Machine Learning Random Forest ApproachXiaoya Guo, Akiko Maehara, Mingming Yang, et al.Pageof 23