D
Dorin Comaniciu
Researcher at Princeton University
Publications - 632
Citations - 43059
Dorin Comaniciu is an academic researcher from Princeton University. The author has contributed to research in topics: Segmentation & Object detection. The author has an hindex of 74, co-authored 622 publications receiving 40541 citations. Previous affiliations of Dorin Comaniciu include Siemens & Rutgers University.
Papers
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Journal ArticleDOI
Early diagnosis of acute coronary syndrome
Hugo A. Katus,André Ziegler,Okan Ekinci,Okan Ekinci,Evangelos Giannitsis,Wendy Gattis Stough,Stephan Achenbach,Stefan Blankenberg,Martina Brueckmann,Martina Brueckmann,Paul O. Collinson,Paul O. Collinson,Dorin Comaniciu,Filippo Crea,Wilfried Dinh,Gregory Ducrocq,Frank A. Flachskampf,Keith A.A. Fox,Matthias G Friedrich,Matthias G Friedrich,Kathy Hebert,Anders Himmelmann,Mark A. Hlatky,Dominik Lautsch,Bertil Lindahl,Dan Lindholm,Nicholas L. Mills,Giorgio Minotti,Martin Möckel,Torbjørn Omland,Veronique Semjonow +30 more
TL;DR: In this article, the authors proposed approaches for the optimal application of early strategies in clinical practice to improve patient care following the review of recent advances in the early diagnosis of acute coronary syndrome.
Patent
Marginal space learning for multi-person tracking over mega pixel imagery
TL;DR: In this article, a method for tracking pedestrians in a video sequence, where each image frame of the video sequence corresponds to a time step, includes using marginal space learning to sample a prior probability distribution p(xt|Zt−1) of multi-person identity assignments given a set of feature measurements from all previous image frames.
Patent
System and method for coronary digital subtraction angiography
TL;DR: In this paper, a method and system for extracting coronary vessels fluoroscopic image sequences using coronary digital subtraction angiography (DSA) was disclosed, where a set of mask images of a coronary region was received, and a sequence of contrast images for the coronary region is received.
Patent
Method and system for catheter detection and tracking in a fluoroscopic image sequence
TL;DR: In this article, a method and system for detecting and tracking an ablation catheter tip in a fluoroscopic image sequence is disclosed, in which the tip candidates are detected in each frame of the image sequence using marginal space learning.
Journal ArticleDOI
3D Printing, Computational Modeling, and Artificial Intelligence for Structural Heart Disease
Dee Dee Wang,Zhen Qian,Marija Vukicevic,Sandy Engelhardt,Arash Kheradvar,Chuck Zhang,Stephen H. Little,Johan W. Verjans,Dorin Comaniciu,William W. O'Neill,Mani A. Vannan +10 more
TL;DR: Transcatheter structural heart interventions are requiring in-depth periprocedural understanding of cardiac pathophysiology and device interactions not afforded by traditional imaging metrics, changing the landscape of physician training and delivery of patient-centric care.