VCBM 12: Eurographics Workshop on Visual Computing for Biology and Medicine

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https://diglib.eg.org/handle/10.2312/464

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Browsing VCBM 12: Eurographics Workshop on Visual Computing for Biology and Medicine by Subject "I.3.6 [Computer Graphics]"

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    Atomistic Visualization of Mesoscopic Whole-Cell Simulations
    (The Eurographics Association, 2012) Falk, Martin; Krone, Michael; Ertl, Thomas; Timo Ropinski and Anders Ynnerman and Charl Botha and Jos Roerdink
    Molecular visualizations are a principal tool for analyzing the results of biochemical simulations. With modern GPU ray casting approaches it is only possible to render several millions of atoms at interactive frame rates unless advanced acceleration methods are employed. But even simplified cell models of whole-cell simulations consist of at least several billion atoms. However, many instances of only a few different proteins occur in the intracellular environment, which is beneficial in order to fit the data into the graphics memory. One model is stored for each protein species and rendered once per instance. The proposed method exploits recent algorithmic advances for particle rendering and the repetitive nature of intracellular proteins to visualize dynamic results from mesoscopic simulations of cellular transport processes. We present two out-of-core optimizations for the interactive visualization of data sets composed of billions of atoms as well as details on the data preparation and the employed rendering techniques. Furthermore, we apply advanced shading methods to improve the image quality including methods to enhance depth and shape perception besides non-photorealistic rendering methods.
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    Constrained Labeling of 2D Slice Data for Reading Images in Radiology
    (The Eurographics Association, 2012) Mogalle, Katja; Tietjen, Christian; Soza, Grzegorz; Preim, Bernhard; Timo Ropinski and Anders Ynnerman and Charl Botha and Jos Roerdink
    An important and underestimated task to support reading of images in radiology is a proper annotation of findings. In radiology reading, 2D slice images from a given modality (e.g. CT or MRI) need to be analyzed carefully by a radiologist, whereas all clinical relevant findings have to be annotated in the images. This includes information in particular for documentation, follow-up investigations and medical team meetings. The main problem of the automatic placement of labels in a clinical context is to find an arrangement of multiple variable-sized labels which guarantees readability, clearness and unambiguity and avoids occlusion of the image itself. Based on a case study of abdominal CT-Images in an oncologic context we analyze the main constraints for label placement in order to extract candidate label positions, evaluate these and determine valid and good label positions. Based on this preprocessing step, different approaches can be applied for placing multiple labels in a scene. We present a new method called Shifting and compare it to other labeling strategies.
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    On the Value of Multi-Volume Visualization for Preoperative Planning of Cerebral AVM Surgery
    (The Eurographics Association, 2012) Weiler, Florian; Rieder, Christian; David, Carlos A.; Wald, Christoph; Hahn, Horst K.; Timo Ropinski and Anders Ynnerman and Charl Botha and Jos Roerdink
    Surgical treatment of cerebral arteriovenous malformations (AVMs) requires thourough preoperative planning for the intervening neurosurgeon. The goal of such planning is to gain a precise understanding of the patho-anatomy of the malformation, specifically about the location and spatial relation of normal and abnormal structures. A key element in this process is the identication and localization of arteries feeding into the lesion, and veins draining it. In this paper, we demonstrate how state-of-the-art techniques from the field of computer graphics and image processing can support neurosurgeons with this task. We address the problem by merging multiple angiographic image sets within a 3D volume rendering pipeline. Datasets from clinical imaging studies were remotely processed at our institute, returned to the institution of origin, and finally visualized in an interactive application, allowing the neurosurgeon to explore the different images simultaneously. Here, we present three case studies along with the medical assessment of an experienced neurosurgeon.
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    Sketch-based Image-independent Editing of 3D Tumor Segmentations using Variational Interpolation
    (The Eurographics Association, 2012) Heckel, Frank; Braunewell, Stefan; Soza, Grzegorz; Tietjen, Christian; Hahn, Horst K.; Timo Ropinski and Anders Ynnerman and Charl Botha and Jos Roerdink
    In the past years sophisticated automatic segmentation algorithms for various medical image segmentation problems have been developed. However, there are always cases where automatic algorithms fail to provide an acceptable segmentation. In these cases the user needs efficient segmentation correction tools, a problem which has not received much attention in research. Cases to be manually corrected are often particularly difficult and the image does often not provide enough information for segmentation, so we present an image-independent method for intuitive sketch-based editing of 3D tumor segmentations. It is based on an object reconstruction using variational interpolation and can be used in any 3D modality, such as CT or MRI. We also discuss sketch-based editing in 2D as well as a hole-correction approach for variational interpolation. Our manual correction algorithm has been evaluated on 89 segmentations of tumors in CT by 2 technical experts with 6+ years of experience in tumor segmentation and assessment. The experts rated the quality of our correction tool as acceptable or better in 92.1% of the cases. They needed a median number of 4 correction steps with one step taking 0.4s on average.