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David J. Sahn

dblp:24/1903 · DBLP profile ↗
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3ranked-venue papers
0as first author
0since 2021 · last 2013
0000-0003-1547-6231ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Graphics, computer vision, multimedia, augmented reality and games · 3Applied, interdisciplinary, general and emerging computing · 2Artificial intelligence and machine learning · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
1 paper
Medical and health informatics · 100%
Computer graphics and multimedia
1 paper
Image and video processing · 100%
Artificial intelligence
1 paper
3D vision · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Medical and health informatics › medical imaging
cardiac imaging
0.112007
Speckle Tracking in 3D Echocardiography with Motion Coherence · CVPR 2007
Image and video processing › motion analysis
motion tracking
0.112007
Speckle Tracking in 3D Echocardiography with Motion Coherence · CVPR 2007
Computer vision › 3D vision › motion perception
motion coherence
0.012007
Speckle Tracking in 3D Echocardiography with Motion Coherence · CVPR 2007

Methods — techniques the papers use, named apart from their topics

motion coherence constraint · 0.2dynamic model · 0.1dynamic models · 0.1
YearPublicationVenuePosition
2013 Cardiac Motion Estimation by Optimizing Transmural Homogeneity of the Myofiber Strain and Its Validation with Multimodal Sequences
David J. Sahn, Xubo B. Song
MICCAI (1)2
2007 Speckle Tracking in 3D Echocardiography with Motion Coherence
abstract
Tracking of speckles in echocardiography enables the study of myocardium deformation, and thus can provide insights about heart structure and function. Most of the current methods are based on 2D speckle tracking, which suffers from errors due to through-plane decorrelation. Speckle tracking in 3D overcomes such limitation. However, 3D speckle tracking is a challenging problem due to relatively low spatial and temporal resolution of 3D echocardiography. To ensure accurate and robust tracking, high level spatial and temporal constraints need to be incorporated. In this paper, we introduce a novel method for speckle tracking in 3D echocardiography. Instead of tracking each speckle independently, we enforce a motion coherence constraint, in conjunction with a dynamic model for the speckles. This method is validated on in vivo porcine hearts, and is proved to be accurate and robust.
Xubo B. Song, Andriy Myronenko, David J. Sahn
CVPR3
2007 LV Motion Tracking from 3D Echocardiography Using Textural and Structural Information
Andriy Myronenko, Xubo B. Song, David J. Sahn
MICCAI (2)3