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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Proceedings ArticleDOI
3D ultrasound tracking of the left ventricle using one-step forward prediction and data fusion of collaborative trackers
TL;DR: This paper proposes a novel one-step forward prediction to generate the motion prior using motion manifold learning, and introduces two collaborative trackers to achieve both temporal consistency and failure recovery.
Proceedings ArticleDOI
Incremental density approximation and kernel-based Bayesian filtering for object tracking
TL;DR: This paper proposes an alternative to the classical particle filter in which the underlying pdf is represented with a semi-parametric method based on a mode finding algorithm using mean-shift, and a mode propagation technique is designed for this new representation for tracking applications.
Book ChapterDOI
Automatic Vertebra Labeling in Large-Scale 3D CT Using Deep Image-to-Image Network with Message Passing and Sparsity Regularization
Dong Yang,Tao Xiong,Daguang Xu,Qiangui Huang,David Liu,S. Kevin Zhou,Zhoubing Xu,Jin-Hyeong Park,Mingqing Chen,Trac D. Tran,Sang Peter Chin,Dimitris N. Metaxas,Dorin Comaniciu +12 more
TL;DR: Zhang et al. as mentioned in this paper proposed an automatic and fast algorithm to localize and label the vertebra centroids in 3D CT volumes using deep image-to-image network (DI2IN).
Book ChapterDOI
Shape regression machine
TL;DR: The effectiveness of SRM is demonstrated using experiments on segmenting the left ventricle endocardium from an echocardiogram of an apical four chamber view and a boosting regression approach that supports real time segmentation is proposed.
Patent
Method and System for Image Based Device Tracking for Co-registration of Angiography and Intravascular Ultrasound Images
TL;DR: In this paper, a method and system for co-registration of angiography data and intra vascular ultrasound (IVUS) data is disclosed, where a vessel branch is detected in an angiogram image and a fluoroscopic image sequence is received while the IVUS transducer is being pulled back through the vessel branch.