VCBM 2021: Eurographics Workshop on Visual Computing for Biology and Medicine

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https://diglib.eg.org/handle/10.2312/2633086

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Browsing VCBM 2021: Eurographics Workshop on Visual Computing for Biology and Medicine by Subject "Computing methodologies"

Now showing 1 - 4 of 4
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    Automatic Cutting and Flattening of Carotid Artery Geometries
    (The Eurographics Association, 2021) Eulzer, Pepe; Richter, Kevin; Meuschke, Monique; Hundertmark, Anna; Lawonn, Kai; ,; Oeltze-Jafra, Steffen and Smit, Noeska N. and Sommer, Björn and Nieselt, Kay and Schultz, Thomas
    We propose a novel method to cut and flatten vascular geometry that results in an intuitive mapping between the 3D and 2D domains. Our approach is fully automatic, and the sole input is the vessel geometry. We aim to simplify parameter analysis on vessel walls for research on vascular disease and computational hemodynamics. We present a use case for the flattening to aid efforts in investigating the pathophysiology of carotid stenoses (vessel constrictions that are a root cause of stroke). To achieve an intuitive mapping, we introduce the notion of natural vessel cuts. They remain on one side of vessel branches, meaning they adhere to the longitudinal direction and thus result in a comprehensible unfolding of the geometry. Vessel branches and endpoints are automatically detected, and a 2D layout configuration is found that retains the original branch layout. We employ a quasi-isometric surface parameterization to map the geometry to the 2D domain as a single patch. The flattened depiction resolves the need for tedious 3D interaction as the whole surface is visible at once.We found this overview particularly beneficial for exploring temporally resolved parameters.
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    Polar Space Based Shape Averaging for Star-shaped Biological Objects
    (The Eurographics Association, 2021) Ruzaeva, Karina; Nöh, Katharina; Berkels, Benjamin; Oeltze-Jafra, Steffen and Smit, Noeska N. and Sommer, Björn and Nieselt, Kay and Schultz, Thomas
    In this paper, we propose an averaging method for expert segmentation proposals of microbial organisms, resulting in a smooth, naturally looking segmentation ground truth. The approach exploits a geometrical property of the majority of the organisms - star-shapedness - and is based on contour averaging in polar space. It is robust and computationally efficient, where robustness is due to the absence of tuneable parameters. Moreover, the algorithm preserves the uncertainty (in terms of the standard deviation) of the experts' opinion, which allows to introduce an uncertainty-aware metric for estimation of the segmentation quality. This metric emphasizes the influence of ground truth regions with low variance. We study the performance of the proposed averaging method on time-lapse microscopy data of Corynebacterium glutamicum and the uncertainty-aware metric on synthetic data.
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    Projection Mapping for In-Situ Surgery Planning by the Example of DIEP Flap Breast Reconstruction
    (The Eurographics Association, 2021) Martschinke, Jana; Klein, Vanessa; Kurth, Philipp; Engel, Klaus; Ludolph, Ingo; Hauck, Theresa; Horch, Raymund; Stamminger, Marc; Oeltze-Jafra, Steffen and Smit, Noeska N. and Sommer, Björn and Nieselt, Kay and Schultz, Thomas
    Nowadays, many surgical procedures require preoperative planning, mostly relying on data from 3D imaging techniques like computed tomography or magnetic resonance imaging. However, preoperative assessment of this data is carried out on the PC (using classical CT/MR viewing software) and not on the patient's body itself. Therefore, surgeons need to transfer both their overall understanding of the patient's individual anatomy and also specific markers and labels for important points from the PC to the patient only with the help of imaginative power or approximative measurement. In order to close the gap between preoperative planning on the PC and surgery on the patient, we propose a system to directly project preoperative knowledge to the body surface by projection mapping. As a result, we are able to display both assigned labels and a volumetric and view-dependent view of the 3D data in-situ. Furthermore, we offer a method to interactively navigate through the data and add 3D markers directly in the projected volumetric view. We demonstrate the benefits of our approach using DIEP flap breast reconstruction as an example. By means of a small pilot study, we show that our method outperforms standard surgical planning in accuracy and can easily be understood and utilized even by persons without any medical knowledge.
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    Shading Style Assessment for Vessel Wall and Lumen Visualization
    (The Eurographics Association, 2021) Ostendorf, Kai; Mastrodicasa, Domenico; Bäumler, Kathrin; Codari, Marina; Turner, Valery; Willemink, Martin J.; Fleischmann, Dominik; Preim, Bernhard; Mistelbauer, Gabriel; Oeltze-Jafra, Steffen and Smit, Noeska N. and Sommer, Björn and Nieselt, Kay and Schultz, Thomas
    Current blood vessel rendering usually depicts solely the surface of vascular structures and does not visualize any interior structures. While this approach is suitable for most applications, certain cardiovascular diseases, such as aortic dissection would benefit from a more comprehensive visualization. In this work, we investigate different shading styles for the visualization of the aortic inner and outer wall, including the dissection flap. Finding suitable shading algorithms, techniques, and appropriate parameters is time-consuming when practitioners fine-tune them manually. Therefore, we build a shading pipeline using wellknown shading algorithms such as Blinn-Phong, Oren-Nayar, Cook-Torrance, Toon, and extended Lit-Sphere shading with techniques such as the Fresnel effect and screen space ambient occlusion. We interviewed six experts from various domains to find the best combination of shadings for preset combinations that maximize user experience and the applicability in clinical settings.