Dr. Ursula Kose Profile

Dr. Ursula Kose

at Philips Medical Systems International BV

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Author

Publications (5)

Proceedings Article | 3 March 2009 Paper

Temporal variations in apparent breast lesion volume in dynamic contrast enhanced breast MR imaging

Thomas Buelow, Rafael Wiemker, Lina Arbash Meinel, Hans Buurman, Ursula Kose, Gillian Newstead

Proceedings Volume 7260, 726029 (2009) https://doi.org/10.1117/12.812220

KEYWORDS: Image segmentation, Breast, Magnetic resonance imaging, Image processing algorithms and systems, Tumors, Mammography, Breast cancer, Cancer, Diagnostics, Algorithm development

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Dynamic Contrast Enhanced Breast MR Imaging (DCE BMRI) has emerged as a modality for breast cancer diagnosis. In this modality a temporal sequence of volume images of the breasts is acquired, where a contrast agent is injected after acquisition of the first 3D image. Since the introduction of the modality, research has been directed at the development of computer-aided support for the diagnostic workup. This includes automatic segmentation of mass-like lesions, lesion characterization, and lesion classification. Robustness, user-independence, and reproducibility of the results of computerized methods are essential for such methods to be acceptable for clinical application. A previously proposed and evaluated computerized lesion segmentation method has been further analyzed in this study. The segmentation method uses as input a subtraction image (post-contrast - pre-contrast) and a user defined region of interest (ROI). Previous evaluation studies investigated the robustness of the segmentation against variations in the user selected ROI. Robustness of the method against variations in the image data itself has so far not been investigated. To fill this gap is the purpose of this study. In this study, the segmentation algorithm was applied to a series of subtraction images built from the pre-contrast volume and all available post-contrast image volumes, successively. This provides set of typically 4-5 delineations per lesion, each based on a different phase of the dynamic sequence. Analysis of the apparent lesion volumes derived from these delineations and comparison to manual delineations showed that computerized segmentation is more robust and reproducible than manual segmentation, even if computer segmentations are computed on subtraction images derived from different dynamic phases of the DCE MRI study, while all manual segmentations of a lesion are derived from one and the same dynamic phase of the study. Furthermore, it could be shown that the rate of apparent change of lesion volume over the course of a DCE MRI study is significantly dependent on the lesion type (benign vs. malignant).

Proceedings Article | 29 March 2007 Paper

Segmentation of suspicious lesions in dynamic contrast-enhanced breast MR images

Thomas Bülow, Lina Arbash Meinel, Rafael Wiemker, Ursula Kose, Akiko Shimauchi, Gillian Newstead

Proceedings Volume 6514, 65140T (2007) https://doi.org/10.1117/12.706537

KEYWORDS: Image segmentation, Breast, Magnetic resonance imaging, Computer aided diagnosis and therapy, Breast cancer, Tumors, Feature extraction, Optical spheres, Diagnostics, Data acquisition

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Proceedings Article | 13 March 2006 Paper

Computational fluid dynamics of abdominal aortic aneurysms with patient-specific inflow boundary conditions

Ursula Kose, Sander de Putter, Romhild Hoogeveen, Marcel Breeuwer

Proceedings Volume 6143, 61432D (2006) https://doi.org/10.1117/12.649755

KEYWORDS: Image segmentation, Magnetic resonance imaging, Visualization, Computer simulations, Computational fluid dynamics, 3D image processing, Blood circulation, Blood, Image registration, Mechanics

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Proceedings Article | 13 March 2006 Paper

Patient-specific models of wall stress in abdominal aortic aneurysm: a comparison between MR and CT

Sander de Putter, Marcel Breeuwer, Frans van de Vosse, Ursula Kose, Frans Gerritsen

Proceedings Volume 6143, 61430D (2006) https://doi.org/10.1117/12.651675

KEYWORDS: Image segmentation, Magnetic resonance imaging, Computed tomography, Modeling, Image resolution, Medical imaging, Biomedical engineering, Error analysis, Arteries, Mercury

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Proceedings Article | 12 April 2005 Paper

Comprehensive combined visualization of anatomy and hemodynamics

Ursula Kose, Kees Visser, Cathy Tryon, Marcel Breeuwer

Proceedings Volume 5744, (2005) https://doi.org/10.1117/12.593585

KEYWORDS: Visualization, Hemodynamics, Image segmentation, Cameras, Blood circulation, Image visualization, Opacity, Volume rendering, Spine, Particles

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