Vladimir Pekar

发表

SU‐GG‐I‐89: Automatic Segmentation of Risk Structures

Daniel Bystrov, Heinrich Schulz, Torbjorn Vik, 2008 .

Fast computation of isosurface contour spectra for volume visualization

Rafael Wiemker, Vladimir Pekar, 2001, CARS.

Automated 3-D PDM construction from segmented images using deformable models

Jürgen Weese, Cristian Lorenz, Michael Kaus, 2003, IEEE Transactions on Medical Imaging.

Automatic knee cartilage delineation using inheritable segmentation

Sebastian P. M. Dries, Daniel Bystrov, Vladimir Pekar, 2008, SPIE Medical Imaging.

TH-C-AUD C-02: Automatic Extraction of Salient Interest Points in 3D Images for Contour Propagation in IGRT

David Jaffray, Vladimir Pekar, S. Allaire, 2008 .

Full orientation invariance and improved feature selectivity of 3D SIFT with application to medical image analysis

Vladimir Pekar, David A. Jaffray, Stéphane Allaire, 2008, 2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops.

Segmentation d'image

Michael Kaus, Vladimir Pekar, Juergen Weese, 2002 .

A method for segmenting a three-dimensional data set with facilitation of user corrections

Holger Timinger, Vladimir Pekar, Michael Philips Int. Kaus, 2003 .

Robust and Efficient Triangulation of Anatomical Surfaces from Medical Images

Cristian Lorenz, Michael Kaus, Vladimir Pekar, 2005, Bildverarbeitung für die Medizin.

Automated 3D and 4D organ delineation for radiation therapy planning in the pelvic area

Vladimir Pekar, Todd McNutt, Michael R. Kaus, 2004, SPIE Medical Imaging.

Detection of point landmarks in 3D medical images via phase congruency model

Vladimir Pekar, Ricardo José Ferrari, David A. Jaffray, 2011, Journal of the Brazilian Computer Society.

Probabilistic Refinement of Model-Based Segmentation: Application to Radiation Therapy Planning of the Head and Neck

Vladimir Pekar, David A. Jaffray, John J. Kim, 2010, MIAR.

Spine Detection and Labeling Using a Parts-Based Graphical Model

Sebastian P. M. Dries, Christoph Schnörr, Daniel Bystrov, 2007, IPMI.

Automated 3D PDM Construction Using Deformable Models

Jürgen Weese, Cristian Lorenz, Michael Kaus, 2001, ICCV.

Segmentation-aided adaptive filtering for metal artifact reduction in radio-therapeutic CT images

Vladimir Pekar, Kai Eck, Lothar Spies, 2004, SPIE Medical Imaging.

Shape Constrained Deformable Models for 3D Medical Image Segmentation

Jürgen Weese, Cristian Lorenz, Michael Kaus, 2001, IPMI.

A feature-based approach for refinement of Model-based segmentation of low contrast structures

Vladimir Pekar, David A. Jaffray, John J. Kim, 2011, 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

Motion Compensation and Plane Tracking for Kinematic MR-Imaging

Daniel Bystrov, Heinrich Schulz, Vladimir Pekar, 2005, CVBIA.

Coupled deformable models with spatially varying features for quantitative assessment of left ventricular function from cardiac MRI

Jens von Berg, Wiro J. Niessen, Vladimir Pekar, 2003, SPIE Medical Imaging.

Fast detection of meaningful isosurfaces for volume data visualization

Rafael Wiemker, Daniel Bystrov, Vladimir Pekar, 2001, Proceedings Visualization, 2001. VIS '01..

A comparison between BEM and FEM for elastic registration of medical images

Karl Rohr, Evgeny Gladilin, H. Siegfried Stiehl, 2006, Image Vis. Comput..

Towards automatic patient positioning and scan planning using continuously moving table MR imaging

Peter Börnert, Daniel Bystrov, Vladimir Pekar, 2009, Magnetic resonance in medicine.

Efficient representation of shape variability using surface-based free-vibration modes

Jürgen Weese, Cristian Lorenz, Vladimir Pekar, 2001, SPIE Medical Imaging.

Automated 3D PDM construction using deformable models

Michael Kaus, Vladimir Pekar, Roel Truyen, 2001, Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001.

Shape-model-based adaptation of 3D deformable meshes for segmentation of medical images

Jürgen Weese, Cristian Lorenz, Vladimir Pekar, 2001, SPIE Medical Imaging.

SU‐GG‐I‐86: Validation of a One‐Click Spine Segmentation Approach for Online Planning of Palliative Radiation Treatment

Vladimir Pekar, David A. Jaffray, Daniel Letourneau, 2008 .

Improving specificity of image features for segmentation with deformable models

Jens von Berg, Vladimir Pekar, Roel Truyen, 2003, SPIE Medical Imaging.

Vessel Segmentation for Visualization of MRA with Blood Pool Contrast Agent

Jürgen Weese, Stewart Young, Vladimir Pekar, 2001, MICCAI.

Feature-driven model-based segmentation

Vladimir Pekar, David A. Jaffray, John J. Kim, 2011, Medical Imaging.

Deformable Image Registration by Adaptive Gaussian Forces

Evgeny Gladilin, Vladimir Pekar, V. Pekar, 2004, ECCV Workshops CVAMIA and MMBIA.

Automated segmentation of the left ventricle in cardiac MRI

Jürgen Weese, Jens von Berg, Wiro J. Niessen, 2004, Medical Image Anal..

Integration of Interactive Corrections to Model-Based Segmentation Algorithms

Holger Timinger, Klaus C. J. Dietmayer, Jens von Berg, 2003, Bildverarbeitung für die Medizin.

Model-Based Segmentation of Anatomical Structures in MR Images of the Head and Neck Area

Michael Kaus, Vladimir Pekar, Marcelo Bacher, 2005, Bildverarbeitung für die Medizin.

Automated planning of MRI scans of knee joints

Sebastian P. M. Dries, Daniel Bystrov, Stewart Young, 2007, SPIE Medical Imaging.

A method of segmenting a three-dimensional structure contained in an object, in particular for medical image analysis

Michael Kaus, Vladimir Pekar, Anja Hennemuth, 2002 .

Modular toolbox for derivative-based medical image registration

Sven Kabus, Astrid Franz, Vladimir Pekar, 2005, SPIE Medical Imaging.

Efficient Visualization of Large Medical Image Datasets on Standard PC Hardware

Gundolf Kiefer, Jürgen Weese, Marc Busch, 2003, VisSym.

Validation of automatic landmark identification for atlas-based segmentation for radiation treatment planning of the head-and-neck region

Heinrich Schulz, Vladimir Pekar, David A. Jaffray, 2008, SPIE Medical Imaging.

Automatic learning-based selection of beam angles in radiation therapy of lung cancer

Vladimir Pekar, Guy Amit, David A. Jaffray, 2014, 2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI).

Automatische Generierung von Bildmerkmalen für die Segmentierung von CT-Bilddaten mit deformierbaren Modellen

Michael Kaus, Vladimir Pekar, F. Hoffmann, 2005, Bildverarbeitung für die Medizin.

Automated Planning of Scan Geometries in Spine MRI Scans

Sebastian P. M. Dries, Daniel Bystrov, Stefan Schmidt, 2007, MICCAI.

Automated Segmentation of the Left Ventricle in Cardiac MRI

Jens von Berg, Wiro J. Niessen, Michael Kaus, 2003, MICCAI.

Estimation of Organ Motion from 4D CT for 4D Radiation Therapy Planning of Lung Cancer

Sven Kabus, Michael Kaus, Vladimir Pekar, 2004, MICCAI.

Automated model-based organ delineation for radiotherapy planning in prostatic region.

Vladimir Pekar, Todd R McNutt, M. Kaus, 2004, International journal of radiation oncology, biology, physics.

Auto-segmentation of normal and target structures in head and neck CT images: a feature-driven model-based approach.

Vladimir Pekar, David A Jaffray, Jason Xie, 2011, Medical physics.

Head and Neck Auto-segmentation Challenge : Segmentation of the Parotid Glands

Vladimir Pekar, David A. Jaffray, Stéphane Allaire, 2010 .

An adaptive irregular grid approach for 3D deformable image registration

Karl Rohr, Evgeny Gladilin, Vladimir Pekar, 2006, Physics in medicine and biology.

Automatic Contour Propagation in Head & Neck IGRT Based on 3D Salient Interest Points

Vladimir Pekar, David A. Jaffray, Stephen Breen, 2008 .

Applications of image processing in image-guided radiation therapy

Vladimir Pekar, Ricardo José Ferrari, R. J. Ferrari, 2008 .

Assessment of a model-based deformable image registration approach for radiation therapy planning.

Vladimir Pekar, David A Jaffray, Kristy K Brock, 2007, International journal of radiation oncology, biology, physics.