L
Lucian Mihai Itu
Researcher at Siemens
Publications - 114
Citations - 1720
Lucian Mihai Itu is an academic researcher from Siemens. The author has contributed to research in topics: Fractional flow reserve & Deep learning. The author has an hindex of 19, co-authored 97 publications receiving 1383 citations. Previous affiliations of Lucian Mihai Itu include Transilvania University of Brașov & Princeton University.
Papers
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Journal ArticleDOI
A machine-learning approach for computation of fractional flow reserve from coronary computed tomography.
Lucian Mihai Itu,Saikiran Rapaka,Tiziano Passerini,Bogdan Georgescu,Chris Schwemmer,Max Schoebinger,Thomas Flohr,Puneet Sharma,Dorin Comaniciu +8 more
TL;DR: A machine-learning-based model for predicting FFR is presented as an alternative to physics-based approaches, and average execution time was reduced by more than 80 times, leading to near real-time assessment of FFR.
Journal ArticleDOI
Coronary CT Angiography–derived Fractional Flow Reserve: Machine Learning Algorithm versus Computational Fluid Dynamics Modeling
Christian Tesche,Carlo N. De Cecco,Stefan Baumann,Matthias Renker,Tindal W. McLaurin,Taylor M. Duguay,Richard R. Bayer nd,Daniel H. Steinberg,Katharine Grant,Christian Canstein,Chris Schwemmer,Max Schoebinger,Lucian Mihai Itu,Saikiran Rapaka,Puneet Sharma,U. Joseph Schoepf +15 more
TL;DR: The FFRML algorithm performs equally in detecting lesion-specific ischemia when compared with the FFRCFD approach, and both methods outperform accuracy of coronary CT angiography and QCA in the detection of flow-limiting stenosis.
Patent
Method and System for Non-Invasive Functional Assessment of Coronary Artery Stenosis
Puneet Sharma,Lucian Mihai Itu,Ali Kamen,Bogdan Georgescu,Xudong Zheng,Huseyin Tek,Dorin Comaniciu,Dominik Bernhardt,Fernando Vega-Higuera,Michael Scheuering +9 more
TL;DR: In this paper, a method and system for non-invasive assessment of coronary artery stenosis is disclosed, where patient-specific anatomical measurements of the coronary arteries are extracted from medical image data of a patient acquired during rest state.
Patent
Method and system for multi-scale anatomical and functional modeling of coronary circulation
TL;DR: In this paper, a multi-scale functional model of coronary circulation is generated based on the patient-specific anatomical model, and virtual intervention simulations are performed using the multiscale function model for decision support and intervention planning.
Patent
Synthetic data-driven hemodynamic determination in medical imaging
Lucian Mihai Itu,Tiziano Passerini,Saikiran Rapaka,Puneet Sharma,Chris Schwemmer,Max Schoebinger,Thomas Redel,Dorin Comaniciu +7 more
TL;DR: In this article, a machine-learnt classifier uses features from medical scan data for a particular patient to estimate the blood flow based on mapping of features to flow learned from the synthetic data.