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Fred S. Azar

dblp:36/3550 · DBLP profile ↗
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4ranked-venue papers
2as first author
0since 2021 · last 2007
—ORCID · none

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

Graphics, computer vision, multimedia, augmented reality and games · 3 · 1 first-authorApplied, interdisciplinary, general and emerging computing · 3 · 2 first-authorArtificial 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%
Theoretical computer science
1 paper
Mathematical optimization · 100%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Medical and health informatics › medical imaging › medical image analysis › image registration
deformable image registration
0.112007
A Unified and Efficient Approach for Free-form Deformable Registration · ICCV 2007
Medical and health informatics › medical imaging
medical image analysis
0.112007
A Unified and Efficient Approach for Free-form Deformable Registration · ICCV 2007
Mathematical optimization › variational methods
energy functional optimization
0.112007
A Unified and Efficient Approach for Free-form Deformable Registration · ICCV 2007
Mathematical optimization
variational methods
0.112007
A Unified and Efficient Approach for Free-form Deformable Registration · ICCV 2007

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

variational method · 0.1partial differential equations · 0.1free-form deformation · 0.1
YearPublicationVenuePosition
2007 A Unified and Efficient Approach for Free-form Deformable Registration
abstract
We propose a novel numerical approach for solving the free-form deformable registration problem. The central idea is to utilize the well understood techniques from variational deformable registration problems. We demonstrate that it is possible to formulate the free-form deformable registration problem as the optimization of an energy functional as in the dense deformation case. This energy functional possesses image distance and regularization terms, which are both functions of the free-form deformation control points. We then setup a semi-backward (implicit) partial differential equation that optimizes the established energy functional. In addition to being mathematically justified, this approach provides both accuracy and speed. Our evaluation on synthetic, real, two dimensional, and three dimensional data demonstrates accuracy and computational effectiveness.
Ali Kamen, Fred S. Azar, Loren Arthur Schwarz, Darko Zikic, Nassir Navab, Eike Rietzel
ICCV2
2003 Local 3D Reconstruction and Augmented Reality Visualization of Free-Hand Ultrasound for Needle Biopsy Procedures
Ali Kamen, Sebastian Vogt 0001, Fred S. Azar, Tobias Sielhorst, Frank Sauer, Heinrich Niemann
MICCAI (2)3
2002 Methods for modeling and predicting mechanical deformations of the breast under external perturbations
Fred S. Azar, Dimitris N. Metaxas, Mitchell D. Schnall
Medical Image Anal.1
2001 Methods for Modeling and Predicting Mechanical Deformations of the Breast Under External Perturbations
Fred S. Azar, Dimitris N. Metaxas, Mitchell D. Schnall
MICCAI1