Browsing by Author "Klingner, Carsten M."

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    A Fully Integrated Pipeline for Visual Carotid Morphology Analysis
    (The Eurographics Association and John Wiley & Sons Ltd., 2023) Eulzer, Pepe; Deylen, Fabienne von; Hsu, Wei-Chan; Wickenhöfer, Ralph; Klingner, Carsten M.; Lawonn, Kai; Bujack, Roxana; Archambault, Daniel; Schreck, Tobias
    Analyzing stenoses of the internal carotids - local constrictions of the artery - is a critical clinical task in cardiovascular disease treatment and prevention. For this purpose, we propose a self-contained pipeline for the visual analysis of carotid artery geometries. The only inputs are computed tomography angiography (CTA) scans, which are already recorded in clinical routine. We show how integrated model extraction and visualization can help to efficiently detect stenoses and we provide means for automatic, highly accurate stenosis degree computation. We directly connect multiple sophisticated processing stages, including a neural prediction network for lumen and plaque segmentation and automatic global diameter computation. We enable interactive and retrospective user control over the processing stages. Our aims are to increase user trust by making the underlying data validatable on the fly, to decrease adoption costs by minimizing external dependencies, and to optimize scalability by streamlining the data processing. We use interactive visualizations for data inspection and adaption to guide the user through the processing stages. The framework was developed and evaluated in close collaboration with radiologists and neurologists. It has been used to extract and analyze over 100 carotid bifurcation geometries and is built with a modular architecture, available as an extendable open-source platform.
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    Visualizing Carotid Stenoses for Stroke Treatment and Prevention
    (The Eurographics Association, 2023) Eulzer, Pepe; Richter, Kevin; Hundertmark, Anna; Meuschke, Monique; Wickenhöfer, Ralph; Klingner, Carsten M.; Lawonn, Kai; Raidou, Renata; Kuhlen, Torsten
    Analyzing carotid stenoses - potentially lethal constrictions of the brain-supplying arteries - is a critical task in clinical stroke treatment and prevention. Determining the ideal type of treatment and point for surgical intervention to minimize stroke risk is considerably challenging. We propose a collection of visual exploration tools to advance the assessment of carotid stenoses in clinical applications and research on stenosis formation. We developed methods to analyze the internal blood flow, anatomical context, vessel wall composition, and to automatically and reliably classify stenosis candidates. We do not presume already segmented and extracted surface meshes but integrate streamlined model extraction and pre-processing along with the result visualizations into a single framework. We connect multiple sophisticated processing stages in one user interface, including a neural prediction network for vessel segmentation and automatic global diameter computation. We enable retrospective user control over each processing stage, greatly simplifying error detection and correction. The framework was developed and evaluated in multiple iterative user studies, involving a group of eight specialists working in stroke care (radiologists and neurologists). It is publicly available, along with a database of over 100 carotid bifurcation geometries that were extracted with the framework from computed tomography data. Further, it is a vital part of multiple ongoing studies investigating stenosis pathophysiology, stroke risk, and the necessity for surgical intervention.