Dr. Sven Kabus Profile

Dr. Sven Kabus

at Philips Research

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Author

Publications (15)

Proceedings Article | 9 March 2018 Paper

Motion compensation for non-gated helical CT: application to lung imaging

M. Grass, R. Bippus, A. Thran, D. Schäfer, S. Kabus, K. Brown

Proceedings Volume 10573, 105733H (2018) https://doi.org/10.1117/12.2292879

KEYWORDS: Computed tomography, Lung imaging, Lung, Image registration, Motion estimation, Scanners, Data acquisition, 3D image reconstruction, CT reconstruction, Reconstruction algorithms

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Proceedings Article | 18 March 2016 Paper

Surface driven biomechanical breast image registration

Björn Eiben, Vasileios Vavourakis, John Hipwell, Sven Kabus, Cristian Lorenz, Thomas Buelow, Norman Williams, M. Keshtgar, David Hawkes

Proceedings Volume 9786, 97860W (2016) https://doi.org/10.1117/12.2216728

KEYWORDS: Image registration, Breast, Modeling, Magnetic resonance imaging, Natural surfaces, Breast cancer, Tissues, Detection and tracking algorithms, Skin, Computed tomography, Nipple, Surgery

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Proceedings Article | 12 March 2014 Paper

Breast deformation modelling: comparison of methods to obtain a patient specific unloaded configuration

Björn Eiben, Vasileios Vavourakis, John Hipwell, Sven Kabus, Cristian Lorenz, Thomas Buelow, David Hawkes

Proceedings Volume 9036, 903615 (2014) https://doi.org/10.1117/12.2043607

KEYWORDS: Breast, Magnetic resonance imaging, Modeling, Computer simulations, Image segmentation, Protactinium, Medical imaging, In vivo imaging, Data modeling, Chest

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Proceedings Article | 4 March 2011 Paper

The impact of motion correction on lesion characterization in DCE breast MR images

Martin Bergtholdt, Sven Kabus, Rafael Wiemker, Thomas Buelow

Proceedings Volume 7963, 79630Z (2011) https://doi.org/10.1117/12.877090

KEYWORDS: Image registration, Image segmentation, Breast, Magnetic resonance imaging, Rigid registration, Tumors, Motion analysis, Computer aided diagnosis and therapy, Image processing algorithms and systems, Visualization

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Proceedings Article | 13 March 2010 Paper

A completely automated processing pipeline for lung and lung lobe segmentation and its application to the LIDC-IDRI data base

Thomas Blaffert, Rafael Wiemker, Hans Barschdorf, Sven Kabus, Tobias Klinder, Cristian Lorenz, Nicole Schadewaldt, Ekta Dharaiya

Proceedings Volume 7623, 762347 (2010) https://doi.org/10.1117/12.844760

KEYWORDS: Lung, Image segmentation, Emphysema, Computed tomography, Databases, Tissues, Image processing algorithms and systems, Lung cancer, Data modeling, Visualization

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Proceedings Article | 3 March 2009 Paper

Follow-up segmentation of lung tumors in PET and CT data

Roland Opfer, Sven Kabus, Torben Schneider, Ingwer Carlsen, Steffen Renisch, Jörg Sabczynski

Proceedings Volume 7260, 72600X (2009) https://doi.org/10.1117/12.811599

KEYWORDS: Tumors, Computed tomography, Image segmentation, Positron emission tomography, Lung, Lung cancer, Cancer, Optical spheres, Radiotherapy, Data acquisition

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Proceedings Article | 28 February 2009 Paper

Agreement of CAD features with expert observer ratings for characterization of pulmonary nodules in CT using the LIDC-IDRI database

Rafael Wiemker, Martin Bergtholdt, Ekta Dharaiya, Sven Kabus, Michael Lee

Proceedings Volume 7260, 72600H (2009) https://doi.org/10.1117/12.811569

KEYWORDS: Databases, Computed tomography, Image segmentation, Computer aided diagnosis and therapy, Lung, Cancer, Medical research, Medical imaging, Biopsy, Statistical analysis

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Proceedings Article | 24 March 2008 Paper

Performance study of a globally elastic locally rigid matching algorithm for follow-up chest CT

Rafael Wiemker, Bartjan de Hoop, Sven Kabus, Hester Gietema, Roland Opfer, Ekta Dharaiya

Proceedings Volume 6917, 691706 (2008) https://doi.org/10.1117/12.765166

KEYWORDS: Lung, Computed tomography, Chest, Image registration, Image segmentation, Collimation, Computer simulations, Medical imaging, Detection and tracking algorithms, Computer aided diagnosis and therapy

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Proceedings Article | 17 March 2008 Paper

Repeatability and noise robustness of spicularity features for computer aided characterization of pulmonary nodules in CT

Rafael Wiemker, Roland Opfer, Thomas Bülow, Sven Kabus, Ekta Dharaiya

Proceedings Volume 6915, 691511 (2008) https://doi.org/10.1117/12.765132

KEYWORDS: Computed tomography, Image segmentation, Computer aided diagnosis and therapy, Lung, Image processing, Solids, Natural surfaces, Diagnostics, Medical imaging, Tumors

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Computer aided characterization aims to support the differential diagnosis of indeterminate pulmonary nodules. A number of published studies have correlated automatically computed features from image processing with clinical diagnoses of malignancy vs. benignity. Often, however, a high number of features was trained on a relatively small number of diagnosed nodules, raising a certain skepticism as to how salient and numerically robust the various features really are. On the way towards computer aided diagnosis which is trusted in clinical practice, the credibility of the individual numerical features has to be carefully established. Nodule volume is the most crucial parameter for nodule characterization, and a number of studies are testing its repeatability. Apart from functional parameters (such as dynamic CT enhancement and PET uptake values), the next most widely used parameter is the surface characteristic (vascularization, spicularity, lobulation, smoothness). In this study, we test the repeatability of two simple surface smoothness features which can discriminate between smoothly delineated nodules and those with a high degree of surface irregularity. Robustness of the completely automatically computed features was tested with respect to the following aspects: (a) repeated CT scan of the same patient with equal dose, (b) repeated CT scan with much lower dose and much higher noise, (c) repeated automatic segmentation of the nodules using varying segmentation parameters, resulting in differing nodule surfaces. The tested nodules (81) were all solid or partially solid and included a high number of sub- and juxtapleural nodules. We found that both tested surface characterization features correlated reasonably well with each other (80%), and that in particular the mean-surface-shape-index showed an excellent repeatability: 98% correlation between equal dose CT scans, 93% between standard-dose and low-dose scan (without systematic shift), and 97% between varying HU-threshold of the automatic segmentation, which makes it a reliable feature to be used in computer aided diagnosis.

Proceedings Article | 12 March 2008 Paper

Intuitive parameter-free visualization of tumor vascularization using rotating connectivity projections

Rafael Wiemker, Thomas Bülow, Roland Opfer, Sven Kabus, Ekta Dharaiya

Proceedings Volume 6916, 69161Z (2008) https://doi.org/10.1117/12.765333

KEYWORDS: Tumors, Visualization, Image segmentation, Lung, Computed tomography, Distortion, Binary data, Medical imaging, Image visualization, Optical inspection

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Proceedings Article | 11 March 2008 Paper

A unified framework for joint registration and segmentation

Konstantin Ens, Jens von Berg, Sven Kabus, Cristian Lorenz, Bernd Fischer

Proceedings Volume 6914, 691406 (2008) https://doi.org/10.1117/12.769157

KEYWORDS: Image segmentation, Image registration, Neuroimaging, Brain, Distance measurement, Image processing, Magnetism, Medical imaging, Magnetic resonance imaging, Alzheimer's disease

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Proceedings Article | 11 March 2008 Paper

Validation and comparison of registration methods for free-breathing 4D lung CT

Torbjørn Vik, Sven Kabus, Jens von Berg, Konstantin Ens, Sebastian Dries, Tobias Klinder, Cristian Lorenz

Proceedings Volume 6914, 69142P (2008) https://doi.org/10.1117/12.767787

KEYWORDS: Image registration, Lung, Phase modulation, Scanning tunneling microscopy, Tumors, Motion estimation, Distance measurement, Image segmentation, Computed tomography, Natural surfaces

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Proceedings Article | 29 March 2007 Paper

Surface based cardiac and respiratory motion extraction for pulmonary structures from multi-phase CT

Jens von Berg, Hans Barschdorf, Thomas Blaffert, Sven Kabus, Cristian Lorenz

Proceedings Volume 6511, 65110Y (2007) https://doi.org/10.1117/12.709395

KEYWORDS: Lung, Natural surfaces, Motion estimation, Heart, Tissues, Computed tomography, Radiotherapy, Motion models, Electrocardiography, Error analysis

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Proceedings Article | 29 April 2005 Paper

Modular toolbox for derivative-based medical image registration

Astrid Franz, Ingwer Carlsen, Sven Kabus, Thomas Netsch, Vladimir Pekar

Proceedings Volume 5747, (2005) https://doi.org/10.1117/12.594066

KEYWORDS: Image registration, Optimization (mathematics), Computed tomography, Algorithm development, Positron emission tomography, Medical imaging, Breast, 3D image processing, Image processing, Medical research

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Proceedings Article | 12 May 2004 Paper

B-spline registration of 3D images with Levenberg-Marquardt optimization

Sven Kabus, Thomas Netsch, Bernd Fischer, Jan Modersitzki

Proceedings Volume 5370, (2004) https://doi.org/10.1117/12.533976

KEYWORDS: Image registration, Magnetic resonance imaging, 3D image processing, Computed tomography, Computing systems, Optimization (mathematics), Mammography, Optical inspection, Positron emission tomography, Medical imaging

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Showing 5 of 15 publications

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