Gabriel Mistelbauer is a senior research engineer in the Department of Radiology at Stanford University School of Medicine since 2022. He received his PhD in computer science in the field of medical visualization in 2013 at TU Wien, Austria. After a postdoctoral appointment at TU Wien, Austria, he joined Otto-von-Guericke University Magdeburg, Germany, as a research associate in 2016. His research focuses on visual computing in medicine and medical image processing, in particular on the analysis of vascular structures.

Honors & Awards

  • Dirk Bartz Prize for Visual Computing in Medicine and Life Sciences (3rd place), Eurographics Medical Prize - Eurographics Conference on Visualization (2023)
  • Best Short Paper Award, Eurographics Workshop on Visual Computing for Biology and Medicine (2021)
  • Image Award (People’s Choice), Eurographics Workshop on Visual Computing for Biology and Medicine (2019)
  • Best Short Paper Award, Eurographics Workshop on Visual Computing for Biology and Medicine (2018)
  • Best Paper Award, Spring Conference on Computer Graphics (2017)
  • Honorable Mention - Best Paper Award, IEEE PacificVis (2017)
  • Honorable Mention - Best Paper Award, Eurographics Workshop on Visual Computing for Biology and Medicine (2015)
  • Honorable Mention - Doctoral Dissertation Award, IEEE VGTC VPG doctoral dissertation award (2015)

Education & Certifications

  • PhD (Dr.techn.), TU Wien, Medical Visualization (2013)
  • MSc (Dipl.-Ing.), TU Wien, Visual Computing (2010)
  • BSc (Bakk.techn.), TU Wien, Media Informatics and Visual Computing (2007)

Professional Interests

- research design and clinical integration
- visual computing, medical visualization, computer graphics
- image processing, medical image processing, machine learning, artificial intelligence
- medical-grade software engineering

Work Experience

  • Research Associate, Otto-von-Guericke University Magdeburg, Department of Simulation and Graphics (2016 - 2022)

    Focus on medical visualization: aortic dissections, vascular morphometry & rendering, dentistry, perfusion data, and prenatal diagnostics


    Magdeburg, Germany

  • Postdoctoral Researcher, TU Wien, Institute of Visual Computing & Human-Centered Technology (2013 - 2016)

    Focus on medical visualization: breast cancer, neuro-radiology & -surgery


    Vienna, Austria

  • PhD Student, TU Wien, Institute of Visual Computing & Human-Centered Technology (2010 - 2013)

    Focus on medical visualization: blood vessel segmentation & visualization


    Vienna, Austria

All Publications

  • Automated cross-sectional view selection in CT angiography of aortic dissections with uncertainty awareness and retrospective clinical annotations. Computers in biology and medicine Pepe, A., Egger, J., Codari, M., Willemink, M. J., Gsaxner, C., Li, J., Roth, P. M., Schmalstieg, D., Mistelbauer, G., Fleischmann, D. 2023; 165: 107365


    Surveillance imaging of patients with chronic aortic diseases, such as aneurysms and dissections, relies on obtaining and comparing cross-sectional diameter measurements along the aorta at predefined aortic landmarks, over time. The orientation of the cross-sectional measuring planes at each landmark is currently defined manually by highly trained operators. Centerline-based approaches are unreliable in patients with chronic aortic dissection, because of the asymmetric flow channels, differences in contrast opacification, and presence of mural thrombus, making centerline computations or measurements difficult to generate and reproduce. In this work, we present three alternative approaches - INS, MCDS, MCDbS - based on convolutional neural networks and uncertainty quantification methods to predict the orientation (ϕ,θ) of such cross-sectional planes. For the monitoring of chronic aortic dissections, we show how a dataset of 162 CTA volumes with overall 3273 imperfect manual annotations routinely collected in a clinic can be efficiently used to accomplish this task, despite the presence of non-negligible interoperator variabilities in terms of mean absolute error (MAE) and 95% limits of agreement (LOA). We show how, despite the large limits of agreement in the training data, the trained model provides faster and more reproducible results than either an expert user or a centerline method. The remaining disagreement lies within the variability produced by three independent expert annotators and matches the current state of the art, providing a similar error, but in a fraction of the time.

    View details for DOI 10.1016/j.compbiomed.2023.107365

    View details for PubMedID 37647783

  • Implicit Modeling of Patient-Specific Aortic Dissections with Elliptic Fourier Descriptors COMPUTER GRAPHICS FORUM Mistelbauer, G., Rossl, C., Baeumler, K., Preim, B., Fleischmann, D. 2021; 40 (3): 423-434

    View details for DOI 10.1111/cgf.14318

    View details for Web of Science ID 000667924000035

  • Semi-automatic vessel detection for challenging cases of peripheral arterial disease. Computers in biology and medicine Mistelbauer, G., Morar, A., Schernthaner, R., Strassl, A., Fleischmann, D., Moldoveanu, F., Groller, M. E. 2021; 133: 104344


    OBJECTIVES: Manual or semi-automated segmentation of the lower extremity arterial tree in patients with Peripheral arterial disease (PAD) remains a notoriously difficult and time-consuming task. The complex manifestations of the disease, including discontinuities of the vascular flow channels, the presence of calcified atherosclerotic plaque in close vicinity to adjacent bone, and the presence of metal or other imaging artifacts currently preclude fully automated vessel identification. New machine learning techniques may alleviate this challenge, but require large and reasonably well segmented training data.METHODS: We propose a novel semi-automatic vessel tracking approach for peripheral arteries to facilitate and accelerate the creation of annotated training data by expert cardiovascular radiologists or technologists, while limiting the number of necessary manual interactions, and reducing processing time. After automatically classifying blood vessels, bones, and other tissue, the relevant vessels are tracked and organized in a tree-like structure for further visualization.RESULTS: We conducted a pilot (N = 9) and a clinical study (N = 24) in which we assess the accuracy and required time for our approach to achieve sufficient quality for clinical application, with our current clinically established workflow as the standard of reference. Our approach enabled expert physicians to readily identify all clinically relevant lower extremity arteries, even in problematic cases, with an average sensitivity of 92.9%, and an average specificity and overall accuracy of 99.9%.CONCLUSIONS: Compared to the clinical workflow in our collaborating hospitals (28:40 ± 7:45 [mm:ss]), our approach (17:24 ± 6:44 [mm:ss]) is on average 11:16 [mm:ss] (39%) faster.

    View details for DOI 10.1016/j.compbiomed.2021.104344

    View details for PubMedID 33915360

  • CT-based True- and False-Lumen Segmentation in Type B Aortic Dissection Using Machine Learning. Radiology. Cardiothoracic imaging Hahn, L. D., Mistelbauer, G., Higashigaito, K., Koci, M., Willemink, M. J., Sailer, A. M., Fischbein, M., Fleischmann, D. 2020; 2 (3): e190179


    Purpose: To develop a segmentation pipeline for segmentation of aortic dissection CT angiograms into true and false lumina on multiplanar reformations (MPRs) perpendicular to the aortic centerline and derive quantitative morphologic features, specifically aortic diameter and true- or false-lumen cross-sectional area.Materials and Methods: An automated segmentation pipeline including two convolutional neural network (CNN) segmentation algorithms was developed. The algorithm derives the aortic centerline, generates MPRs orthogonal to the centerline, and segments the true and false lumina. A total of 153 CT angiograms obtained from 45 retrospectively identified patients (mean age, 50 years; range, 22-79 years) were used to train (n = 103), validate (n = 22), and test (n = 28) the CNN pipeline. Accuracy was evaluated by using the Dice similarity coefficient (DSC). Segmentations were then used to derive the maximal diameter of test-set patients and cross-sectional area profiles of the true and false lumina.Results: The segmentation pipeline yielded a mean DSC of 0.873 ± 0.056 for the true lumina and 0.894 ± 0.040 for the false lumina of test-set cases. Automated maximal diameter measurements correlated well with manual measurements (R 2 = 0.95). Profiles of cross-sectional diameter, true-lumen area, and false-lumen area over several follow-up examinations were derived.Conclusion: A segmentation pipeline was used to accurately identify true and false lumina on CT angiograms of aortic dissection. These segmentations can be used to obtain diameter and other morphologic parameters for surveillance and risk stratification.Supplemental material is available for this article.© RSNA, 2020.

    View details for DOI 10.1148/ryct.2020190179

    View details for PubMedID 33778582

  • Popup-Plots: Warping Temporal Data Visualization IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS Schmidt, J., Fleischmann, D., Preim, B., Braendle, N., Mistelbauer, G. 2019; 25 (7): 2443–57


    Temporal data visualization is used to analyze dependent variables that vary over time, with time being an independent variable. Visualizing temporal data is inherently difficult, due to the many aspects that need to be communicated to the users (e.g., time and variable changes). This is an important topic in visualization, and a wide range of visualization techniques dealing with different tasks have already been designed. In this paper we propose popup-plots, a novel concept where the common interaction of 3D rotation is used to navigate through the data. This allows the users to view the data from different perspectives without having to learn and adapt to new interaction concepts. Popup-plots are therefore a novel method for visualizing and interacting with dependent variables over time. We extend 2D plots with the temporal information by bending the space according to the time. The bending is calculated based on a spherical coordinates approach, which is continuously influenced by the viewing direction towards the plot. Hence, the plot can be viewed from various angles with seamless transitions in between, offering the possibility to analyze different aspects of the represented data. As the current viewing direction is inherently depicted by the shape of the data, the users are able to deduce which part of the data is currently viewed. The temporal information is encoded into the visualization itself, resembling annual rings of a tree. We demonstrate our method by applying it to data from two different domains, comprising measurements at spatial positions over time, and we also evaluated the usability of our solution.

    View details for DOI 10.1109/TVCG.2018.2841385

    View details for Web of Science ID 000469838700009

    View details for PubMedID 29993580

  • AR in VR: assessing surgical augmented reality visualizations in a steerable virtual reality environment INTERNATIONAL JOURNAL OF COMPUTER ASSISTED RADIOLOGY AND SURGERY Hettig, J., Engelhardt, S., Hansen, C., Mistelbauer, G. 2018; 13 (11): 1717-1725


    PURPOSE  : Augmented reality (AR) has emerged as a promising approach to support surgeries; however, its application in real world scenarios is still very limited. Besides sophisticated registration tasks that need to be solved, surgical AR visualizations have not been studied in a standardized and comparative manner. To foster the development of future AR applications, a steerable framework is urgently needed to rapidly evaluate new visualization techniques, explore their individual parameter spaces and define relevant application scenarios. METHODS  : Inspired by its beneficial usage in the automotive industry, the underlying concept of virtual reality (VR) is capable of transforming complex real environments into controllable virtual ones. We present an interactive VR framework, called Augmented Visualization Box (AVB), in which visualizations for AR can be systematically investigated without explicitly performing an error-prone registration. As use case, a virtual laparoscopic scenario with anatomical surface models was created in a computer game engine. In a study with eleven surgeons, we analyzed this VR setting under different environmental factors and its applicability for a quantitative assessment of different AR overlay concepts. RESULTS  : According to the surgeons, the visual impression of the VR scene is mostly influenced by 2D surface details and lighting conditions. The AR evaluation shows that, depending on the visualization used and its capability to encode depth, 37% to 91% of the experts made wrong decisions, but were convinced of their correctness. These results show that surgeons have more confidence in their decisions, although they are wrong, when supported by AR visualizations. CONCLUSION  : With AVB, intraoperative situations are realistically simulated to quantitatively benchmark current AR overlay methods. Successful surgical task execution in an AR system can only be facilitated if visualizations are customized toward the surgical task.

    View details for DOI 10.1007/s11548-018-1825-4

    View details for Web of Science ID 000451461700004

    View details for PubMedID 30043197

  • Quantitative metrics of the LV trabeculated layer by cardiac CT and cardiac MRI in patients with suspected noncompaction cardiomyopathy. European radiology Manohar, A., Vigneault, D. M., Kwon, D. H., Caliskan, K., Budde, R. P., Hirsch, A., Lee, S. P., Lee, W., Owens, A., Litt, H., Haddad, F., Mistelbauer, G., Wheeler, M., Rubin, D., Tang, W. H., Nieman, K. 2023


    To compare cardiac computed tomography (CCT) and cardiac magnetic resonance (CMR) for the quantitative assessment of the left ventricular (LV) trabeculated layer in patients with suspected noncompaction cardiomyopathy (NCCM).Subjects with LV excessive trabeculation who underwent both CMR and CCT imaging as part of the prospective international multicenter NONCOMPACT clinical study were included. For each subject, short-axis CCT and CMR slices were matched. Four quantitative metrics were estimated: 1D noncompacted-to-compacted ratio (NCC), trabecular-to-myocardial area ratio (TMA), trabecular-to-endocardial cavity area ratio (TCA), and trabecular-to-myocardial volume ratio (TMV). In 20 subjects, end-diastolic and mid-diastolic CCT images were compared for the quantification of the trabeculated layer. Relationships between the metrics were investigated using linear regression models and Bland-Altman analyses.Forty-eight subjects (49.9 ± 12.8 years; 28 female) were included in this study. NCC was moderately correlated (r = 0.62), TMA and TMV were strongly correlated (r = 0.78 and 0.78), and TCA had excellent correlation (r = 0.92) between CMR and CCT, with an underestimation bias from CCT of 0.3 units, and 5.1, 4.8, and 5.4 percent-points for the 4 metrics, respectively. TMA, TCA, and TMV had excellent correlations (r = 0.93, 0.96, 0.94) and low biases (- 3.8, 0.8,  - 3.8 percent-points) between the end-diastolic and mid-diastolic CCT images.TMA, TCA, and TMV metrics of the LV trabeculated layer in patients with suspected NCCM demonstrated high concordance between CCT and CMR images. TMA and TCA were highly reproducible and demonstrated minimal differences between mid-diastolic and end-diastolic CCT images.The results indicate similarity of CCT to CMR for quantifying the LV trabeculated layer, and the small differences in quantification between end-diastole and mid-diastole demonstrate the potential for quantifying the LV trabeculated layer from clinically performed coronary CT angiograms.• Data on cardiac CT for quantifying the left ventricular trabeculated layer are limited. • Cardiac CT yielded highly reproducible metrics of the left ventricular trabeculated layer that correlated well with metrics defined by cardiac MR. • Cardiac CT appears to be equivalent to cardiac MR for the quantification of the left ventricular trabeculated layer.

    View details for DOI 10.1007/s00330-023-10526-1

    View details for PubMedID 38114847

    View details for PubMedCentralID 10317841

  • Artificial Intelligence Applications in Aortic Dissection Imaging. Seminars in roentgenology Mastrodicasa, D., Codari, M., Bäumler, K., Sandfort, V., Shen, J., Mistelbauer, G., Hahn, L. D., Turner, V. L., Desjardins, B., Willemink, M. J., Fleischmann, D. 2022; 57 (4): 357-363

    View details for DOI 10.1053/

    View details for PubMedID 36265987

  • Inter-observer variability of expert-derived morphologic risk predictors in aortic dissection. European radiology Willemink, M. J., Mastrodicasa, D., Madani, M. H., Codari, M., Chepelev, L. L., Mistelbauer, G., Hanneman, K., Ouzounian, M., Ocazionez, D., Afifi, R. O., Lacomis, J. M., Lovato, L., Pacini, D., Folesani, G., Hinzpeter, R., Alkadhi, H., Stillman, A. E., Sailer, A. M., Turner, V. L., Hinostroza, V., Baumler, K., Chin, A. S., Burris, N. S., Miller, D. C., Fischbein, M. P., Fleischmann, D. 2022


    OBJECTIVES: Establishing the reproducibility of expert-derived measurements on CTA exams of aortic dissection is clinically important and paramount for ground-truth determination for machine learning.METHODS: Four independent observers retrospectively evaluated CTA exams of 72 patients with uncomplicated Stanford type B aortic dissection and assessed the reproducibility of a recently proposed combination of four morphologic risk predictors (maximum aortic diameter, false lumen circumferential angle, false lumen outflow, and intercostal arteries). For the first inter-observer variability assessment, 47 CTA scans from one aortic center were evaluated by expert-observer 1 in an unconstrained clinical assessment without a standardized workflow and compared to a composite of three expert-observers (observers 2-4) using a standardized workflow. A second inter-observer variability assessment on 30 out of the 47 CTA scans compared observers 3 and 4 with a constrained, standardized workflow. A third inter-observer variability assessment was done after specialized training and tested between observers 3 and 4 in an external population of 25 CTA scans. Inter-observer agreement was assessed with intraclass correlation coefficients (ICCs) and Bland-Altman plots.RESULTS: Pre-training ICCs of the four morphologic features ranged from 0.04 (-0.05 to 0.13) to 0.68 (0.49-0.81) between observer 1 and observers 2-4 and from 0.50 (0.32-0.69) to 0.89 (0.78-0.95) between observers 3 and 4. ICCs improved after training ranging from 0.69 (0.52-0.87) to 0.97 (0.94-0.99), and Bland-Altman analysis showed decreased bias and limits of agreement.CONCLUSIONS: Manual morphologic feature measurements on CTA images can be optimized resulting in improved inter-observer reliability. This is essential for robust ground-truth determination for machine learning models.KEY POINTS: Clinical fashion manual measurements of aortic CTA imaging features showed poor inter-observer reproducibility. A standardized workflow with standardized training resulted in substantial improvements with excellent inter-observer reproducibility. Robust ground truth labels obtained manually with excellent inter-observer reproducibility are key to develop reliable machine learning models.

    View details for DOI 10.1007/s00330-022-09056-z

    View details for PubMedID 36029344

  • Deep Learning-Based 3D Segmentation of True Lumen, False Lumen, and False Lumen Thrombosis in Type-B Aortic Dissection. Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Wobben, L. D., Codari, M., Mistelbauer, G., Pepe, A., Higashigaito, K., Hahn, L. D., Mastrodicasa, D., Turner, V. L., Hinostroza, V., Baumler, K., Fischbein, M. P., Fleischmann, D., Willemink, M. J. 2021; 2021: 3912-3915


    Patients with initially uncomplicated typeB aortic dissection (uTBAD) remain at high risk for developing late complications. Identification of morphologic features for improving risk stratification of these patients requires automated segmentation of computed tomography angiography (CTA) images. We developed three segmentation models utilizing a 3D residual U-Net for segmentation of the true lumen (TL), false lumen (FL), and false lumen thrombosis (FLT). Model 1 segments all labels at once, whereas model 2 segments them sequentially. Best results for TL and FL segmentation were achieved by model 2, with median (interquartiles) Dice similarity coefficients (DSC) of 0.85 (0.77-0.88) and 0.84 (0.82-0.87), respectively. For FLT segmentation, model 1 was superior to model 2, with median (interquartiles) DSCs of 0.63 (0.40-0.78). To purely test the performance of the network to segment FLT, a third model segmented FLT starting from the manually segmented FL, resulting in median (interquartiles) DSCs of 0.99 (0.98-0.99) and 0.85 (0.73-0.94) for patent FL and FLT, respectively. While the ambiguous appearance of FLT on imaging remains a significant limitation for accurate segmentation, our pipeline has the potential to help in segmentation of aortic lumina and thrombosis in uTBAD patients.Clinical relevance- Most predictors of aortic dissection (AD) degeneration are identified through anatomical modeling, which is currently prohibitive in clinical settings due to the timeintense human interaction. False lumen thrombosis, which often develops in patients with type B AD, has proven to show significant prognostic value for predicting late adverse events. Our automated segmentation algorithm offers the potential of personalized treatment for AD patients, leading to an increase in long-term survival.

    View details for DOI 10.1109/EMBC46164.2021.9631067

    View details for PubMedID 34892087

  • Visual Analytics in Dental Aesthetics Amirkhanov, A., Bernhard, M., Karimov, A., Stiller, S., Geier, A., Groller, M., Mistelbauer, G. WILEY. 2020: 635-646

    View details for DOI 10.1111/cgf.14174

    View details for Web of Science ID 000594502700054

  • Single-stage bone resection and cranioplastic reconstruction: comparison of a novel software-derived PEEK workflow with the standard reconstructive method INTERNATIONAL JOURNAL OF ORAL AND MAXILLOFACIAL SURGERY Dodier, P., Winter, F., Auzinger, T., Mistelbauer, G., Frischer, J. M., Wang, W., Mallouhi, A., Marik, W., Wolfsberger, S., Reissig, L., Hammadi, F., Matula, C., Baumann, A., Bavinzski, G. 2020; 49 (8): 1007-1015


    The combined resection of skull-infiltrating tumours and immediate cranioplastic reconstruction predominantly relies on freehand-moulded solutions. Techniques that enable this procedure to be performed easily in routine clinical practice would be useful. A cadaveric study was developed in which a new software tool was used to perform single-stage reconstructions with prefabricated implants after the resection of skull-infiltrating pathologies. A novel 3D visualization and interaction framework was developed to create 10 virtual craniotomies in five cadaveric specimens. Polyether ether ketone (PEEK) implants were manufactured according to the bone defects. The image-guided craniotomy was reconstructed with PEEK and compared to polymethyl methacrylate (PMMA). Navigational accuracy and surgical precision were assessed. The PEEK workflow resulted in up to 10-fold shorter reconstruction times than the standard technique. Surgical precision was reflected by the mean 1.1±0.29mm distance between the virtual and real craniotomy, with submillimetre precision in 50%. Assessment of the global offset between virtual and actual craniotomy revealed an average shift of 4.5±3.6mm. The results validated the 'elective single-stage cranioplasty' technique as a state-of-the-art virtual planning method and surgical workflow. This patient-tailored workflow could significantly reduce surgical times compared to the traditional, intraoperative acrylic moulding method and may be an option for the reconstruction of bone defects in the craniofacial region.

    View details for DOI 10.1016/j.ijom.2019.11.011

    View details for Web of Science ID 000556819800005

    View details for PubMedID 31866145

  • Knowledge-Assisted Comparative Assessment of Breast Cancer using Dynamic Contrast-Enhanced Magnetic Resonance Imaging COMPUTER GRAPHICS FORUM Nie, K., Baltzer, P., Preim, B., Mistelbauer, G. 2020; 39 (3): 13-23

    View details for DOI 10.1111/cgf.13959

    View details for Web of Science ID 000549627300002

  • Augmenting Node-Link Diagrams with Topographic Attribute Maps COMPUTER GRAPHICS FORUM Preiner, R., Schmidt, J., Kroesl, K., Schreck, T., Mistelbauer, G. 2020; 39 (3): 369-381

    View details for DOI 10.1111/cgf.13987

    View details for Web of Science ID 000549627300030

  • Novel Software-Derived Workflow in Extracranial-Intracranial Bypass Surgery Validated by Transdural Indocyanine Green Videoangiography WORLD NEUROSURGERY Dodier, P., Auzinger, T., Mistelbauer, G., Wang, W., Ferraz-Leite, H., Gruber, A., Marik, W., Winter, F., Fischer, G., Frischer, J. M., Bavinzski, G. 2020; 134: E892-E902


    The introduction of image-guided methods to bypass surgery has resulted in optimized preoperative identification of the recipients and excellent patency rates. However, the recently presented methods have also been resource-consuming. In the present study, we have reported a cost-efficient planning workflow for extracranial-intracranial (EC-IC) revascularization combined with transdural indocyanine green videoangiography (tICG-VA).We performed a retrospective review at a single tertiary referral center from 2011 to 2018. A novel software-derived workflow was applied for 25 of 92 bypass procedures during the study period. The precision and accuracy were assessed using tICG-VA identification of the cortical recipients and a comparison of the virtual and actual data. The data from a control group of 25 traditionally planned procedures were also matched.The intraoperative transfer time of the calculated coordinates averaged 0.8 minute (range, 0.4-1.9 minutes). The definitive recipients matched the targeted branches in 80%, and a neighboring branch was used in 16%. Our workflow led to a significant craniotomy size reduction in the study group compared with that in the control group (P = 0.005). tICG-VA was successfully applied in 19 cases. An average of 2 potential recipient arteries were identified transdurally, resulting in tailored durotomy and 3 craniotomy adjustments. Follow-up patency results were available for 49 bypass surgeries, comprising 54 grafts. The overall patency rate was 91% at a median follow-up period of 26 months. No significant difference was found in the patency rate between the study and control groups (P = 0.317).Our clinical results have validated the presented planning and surgical workflow and support the routine implementation of tICG-VA for recipient identification before durotomy.

    View details for DOI 10.1016/j.wneu.2019.11.038

    View details for Web of Science ID 000512878200104

    View details for PubMedID 31733380

  • Fluid-structure interaction simulations of patient-specific aortic dissection. Biomechanics and modeling in mechanobiology Baumler, K., Vedula, V., Sailer, A. M., Seo, J., Chiu, P., Mistelbauer, G., Chan, F. P., Fischbein, M. P., Marsden, A. L., Fleischmann, D. 2020


    Credible computational fluid dynamic (CFD) simulations of aortic dissection are challenging, because the defining parallel flow channels-the true and the false lumen-are separated from each other by a more or less mobile dissection membrane, which is made up of a delaminated portion of the elastic aortic wall. We present a comprehensive numerical framework for CFD simulations of aortic dissection, which captures the complex interplay between physiologic deformation, flow, pressures, and time-averaged wall shear stress (TAWSS) in a patient-specific model. Our numerical model includes (1) two-way fluid-structure interaction (FSI) to describe the dynamic deformation of the vessel wall and dissection flap; (2) prestress and (3) external tissue support of the structural domain to avoid unphysiologic dilation of the aortic wall and stretching of the dissection flap; (4) tethering of the aorta by intercostal and lumbar arteries to restrict translatory motion of the aorta; and a (5) independently defined elastic modulus for the dissection flap and the outer vessel wall to account for their different material properties. The patient-specific aortic geometry is derived from computed tomography angiography (CTA). Three-dimensional phase contrast magnetic resonance imaging (4D flow MRI) and the patient's blood pressure are used to inform physiologically realistic, patient-specific boundary conditions. Our simulations closely capture the cyclical deformation of the dissection membrane, with flow simulations in good agreement with 4D flow MRI. We demonstrate that decreasing flap stiffness from [Formula: see text] to [Formula: see text] kPa (a) increases the displacement of the dissection flap from 1.4 to 13.4 mm, (b) decreases the surface area of TAWSS by a factor of 2.3, (c) decreases the mean pressure difference between true lumen and false lumen by a factor of 0.63, and (d) decreases the true lumen flow rate by up to 20% in the abdominal aorta. We conclude that the mobility of the dissection flap substantially influences local hemodynamics and therefore needs to be accounted for in patient-specific simulations of aortic dissection. Further research to accurately measure flap stiffness and its local variations could help advance future CFD applications.

    View details for DOI 10.1007/s10237-020-01294-8

    View details for PubMedID 31993829

  • ManyLands: A Journey Across 4D Phase Space of Trajectories COMPUTER GRAPHICS FORUM Amirkhanov, A., Kosiuk, I., Szmolyan, P., Amirkhanov, A., Mistelbauer, G., Groeller, M., Raidou, R. G. 2019; 38 (7): 191-202

    View details for DOI 10.1111/cgf.13828

    View details for Web of Science ID 000496351100018

  • A Survey of Flattening-Based Medical Visualization Techniques Kreiser, J., Meuschke, M., Mistelbauer, G., Preim, B., Ropinski, T. WILEY. 2018: 597-624

    View details for DOI 10.1111/cgf.13445

    View details for Web of Science ID 000438024300051

  • Multipath Curved Planar Reformations of Peripheral CT Angiography: Diagnostic Accuracy and Time Efficiency CARDIOVASCULAR AND INTERVENTIONAL RADIOLOGY Schreiner, M. M., Platzgummer, H., Unterhumer, S., Weber, M., Mistelbauer, G., Groeller, E., Loewe, C., Schernthaner, R. E. 2018; 41 (5): 718-725


    To compare diagnostic performance and time efficiency between 3D multipath curved planar reformations (mpCPRs) and axial images of CT angiography for the pre-interventional assessment of peripheral arterial disease (PAD), with digital subtraction angiography as the standard of reference.Forty patients (10 females, mean age 72 years), referred to CTA prior to endovascular treatment of PAD, were prospectively included and underwent peripheral CT angiography. A semiautomated toolbox was used to render mpCPRs. Twenty-one arterial segments were defined in each leg; for each segment, the presence of stenosis > 70% was assessed on mpCPRs and axial images by two readers, independently, with digital subtraction angiography as gold standard.Both readers reached lower sensitivity (Reader 1: 91 vs. 94%, p = 0.08; Reader 2: 89 vs. 93%, p = 0.03) but significantly higher specificity (Reader 1: 94 vs. 89%, p < 0.01; Reader 2: 96 vs. 95%, p = 0.01) with mpCPRs than with axial images. Reader 1 achieved significantly higher accuracy with mpCPRs (93 vs. 91%, p = 0.02), and Reader 2 had similar overall accuracy in both evaluations (94 vs. 94%, p = 0.96). Both readers read mpCPRs significantly faster than axial images (Reader 1: 5'45″ based on mpCPRs vs. 7'40″ based on axial images; Reader 2: 4'41″ based on mpCPRs vs. 6'57″ based on axial images; p < 0.01).mpCPRs are a promising 3D reformation technique that facilitates a fast assessment of PAD with high diagnostic accuracy.

    View details for DOI 10.1007/s00270-017-1846-3

    View details for Web of Science ID 000428802400008

    View details for PubMedID 29218656

    View details for PubMedCentralID PMC5876266

  • Data-sensitive visual navigation Mindek, P., Mistelbauer, G., Groeller, E., Bruckner, S. PERGAMON-ELSEVIER SCIENCE LTD. 2017: 77-85
  • Visual Quantification of the Circle of Willis: An Automated Identification and Standardized Representation COMPUTER GRAPHICS FORUM Miao, H., Mistelbauer, G., Nasel, C., Groeller, M. E. 2017; 36 (6): 393-404

    View details for DOI 10.1111/cgf.12988

    View details for Web of Science ID 000408634200024

  • A BMI-adjusted ultra-low-dose CT angiography protocol for the peripheral arteries-Image quality, diagnostic accuracy and radiation exposure EUROPEAN JOURNAL OF RADIOLOGY Schreiner, M. M., Platzgummer, H., Unterhumer, S., Weber, M., Mistelbauer, G., Loewe, C., Schernthaner, R. E. 2017; 93: 149-156


    To investigate radiation exposure, objective image quality, and the diagnostic accuracy of a BMI-adjusted ultra-low-dose CT angiography (CTA) protocol for the assessment of peripheral arterial disease (PAD), with digital subtraction angiography (DSA) as the standard of reference.In this prospective, IRB-approved study, 40 PAD patients (30 male, mean age 72 years) underwent CTA on a dual-source CT scanner at 80kV tube voltage. The reference amplitude for tube current modulation was personalized based on the body mass index (BMI) with 120 mAs for [BMI≤25] or 150 mAs for [2570%) was assessed by two readers independently and compared to subsequent DSA. Radiation exposure was assessed with the computed tomography dose index (CTDIvol) and the dosis-length product (DLP). Objective image quality was assessed via contrast- and signal-to-noise ratio (CNR and SNR) measurements. Radiation exposure and image quality were compared between the BMI groups and between the BMI-adjusted ultra-low-dose protocol and the low-dose institutional standard protocol (ISP).The BMI-adjusted ultra-low-dose protocol reached high diagnostic accuracy values of 94% for Reader 1 and 93% for Reader 2. Moreover, in comparison to the ISP, it showed significantly (p<0.001) lower CTDIvol (1.97±0.55mGy vs. 4.18±0.62 mGy) and DLP (256±81mGy x cm vs. 544±83mGy x cm) but similar image quality (p=0.37 for CNR). Furthermore, image quality was similar between BMI groups (p=0.86 for CNR).A CT protocol that incorporates low kV settings with a personalized (BMI-adjusted) reference amplitude for tube current modulation and iterative reconstruction enables very low radiation exposure CTA, while maintaining good image quality and high diagnostic accuracy in the assessment of PAD.

    View details for DOI 10.1016/j.ejrad.2017.06.002

    View details for Web of Science ID 000405361400022

    View details for PubMedID 28668409

  • Placenta Maps: In Utero Placental Health Assessment of the Human Fetus Miao, H., Mistelbauer, G., Karimov, A., Alansary, A., Davidson, A., Lloyd, D. A., Damodaram, M., Story, L., Hutter, J., Hajnal, J. V., Rutherford, M., Preim, B., Kainz, B., Groeller, M. IEEE COMPUTER SOC. 2017: 1612-1623


    The human placenta is essential for the supply of the fetus. To monitor the fetal development, imaging data is acquired using (US). Although it is currently the gold-standard in fetal imaging, it might not capture certain abnormalities of the placenta. (MRI) is a safe alternative for the in utero examination while acquiring the fetus data in higher detail. Nevertheless, there is currently no established procedure for assessing the condition of the placenta and consequently the fetal health. Due to maternal respiration and inherent movements of the fetus during examination, a quantitative assessment of the placenta requires fetal motion compensation, precise placenta segmentation and a standardized visualization, which are challenging tasks. Utilizing advanced motion compensation and automatic segmentation methods to extract the highly versatile shape of the placenta, we introduce a novel visualization technique that presents the fetal and maternal side of the placenta in a standardized way. Our approach enables physicians to explore the placenta even in utero. This establishes the basis for a comparative assessment of multiple placentas to analyze possible pathologic arrangements and to support the research and understanding of this vital organ. Additionally, we propose a three-dimensional structure-aware surface slicing technique in order to explore relevant regions inside the placenta. Finally, to survey the applicability of our approach, we consulted clinical experts in prenatal diagnostics and imaging. We received mainly positive feedback, especially the applicability of our technique for research purposes was appreciated.

    View details for DOI 10.1109/TVCG.2017.2674938

    View details for Web of Science ID 000400527500005

    View details for PubMedID 28252405

  • Computed Tomography Imaging Features in Acute Uncomplicated Stanford Type-B Aortic Dissection Predict Late Adverse Events CIRCULATION-CARDIOVASCULAR IMAGING Sailer, A. M., Van Kuijk, S. M., Nelemans, P. J., Chin, A. S., Kino, A., Huininga, M., Schmidt, J., Mistelbauer, G., Baeumler, K., Chiu, P., Fischbein, M. P., Dake, M. D., Miller, D. C., Schurink, G. W., Fleischmann, D. 2017; 10 (4)


    Medical treatment of initially uncomplicated acute Stanford type-B aortic dissection is associated with a high rate of late adverse events. Identification of individuals who potentially benefit from preventive endografting is highly desirable.The association of computed tomography imaging features with late adverse events was retrospectively assessed in 83 patients with acute uncomplicated Stanford type-B aortic dissection, followed over a median of 850 (interquartile range 247-1824) days. Adverse events were defined as fatal or nonfatal aortic rupture, rapid aortic growth (>10 mm/y), aneurysm formation (≥6 cm), organ or limb ischemia, or new uncontrollable hypertension or pain. Five significant predictors were identified using multivariable Cox regression analysis: connective tissue disease (hazard ratio [HR] 2.94, 95% confidence interval [CI]: 1.29-6.72; P=0.01), circumferential extent of false lumen in angular degrees (HR 1.03 per degree, 95% CI: 1.01-1.04, P=0.003), maximum aortic diameter (HR 1.10 per mm, 95% CI: 1.02-1.18, P=0.015), false lumen outflow (HR 0.999 per mL/min, 95% CI: 0.998-1.000; P=0.055), and number of intercostal arteries (HR 0.89 per n, 95% CI: 0.80-0.98; P=0.024). A prediction model was constructed to calculate patient specific risk at 1, 2, and 5 years and to stratify patients into high-, intermediate-, and low-risk groups. The model was internally validated by bootstrapping and showed good discriminatory ability with an optimism-corrected C statistic of 70.1%.Computed tomography imaging-based morphological features combined into a prediction model may be able to identify patients at high risk for late adverse events after an initially uncomplicated type-B aortic dissection.

    View details for DOI 10.1161/CIRCIMAGING.116.005709

    View details for PubMedID 28360261

  • New hybrid reformations of peripheral CT angiography: do we still need axial images? CLINICAL IMAGING Schernthaner, R., Wolf, F., Mistelbauer, G., Weber, M., Sramek, M., Groeller, E., Loewe, C. 2015; 39 (4): 603-607


    To quantify the detectability of peripheral artery stenosis on hybrid CT angiography (CTA) reformations.Hybrid reformations were developed by combining multipath curved planar reformations (mpCPR) and maximum intensity projections (MIP). Fifty peripheral CTAs were evaluated twice: either with MIP, mpCPR and axial images or with hybrid reformations only. Digital subtraction angiography served as gold standard.Using hybrid reformations, two independent readers detected 88.0% and 81.3% of significant stenosis, respectively. However, CTA including axial images detected statistically significant more lesions (98%).Peripheral CTA reading including axial images is still recommended. Further improvement of these hybrid reformations is necessary.

    View details for DOI 10.1016/j.clinimag.2015.03.005

    View details for Web of Science ID 000356906300011

    View details for PubMedID 25825345

  • Guided Volume Editing based on Histogram Dissimilarity COMPUTER GRAPHICS FORUM Karimov, A., Mistelbauer, G., Auzinger, T., Bruckner, S. 2015; 34 (3): 91-100

    View details for DOI 10.1111/cgf.12621

    View details for Web of Science ID 000358328200012

  • Vessel Visualization using Curved Surface Reformation Auzinger, T., Mistelbauer, G., Baclija, I., Schernthaner, R., Koechl, A., Wimmer, M., Groeller, M., Bruckner, S. IEEE COMPUTER SOC. 2013: 2858-2867


    Visualizations of vascular structures are frequently used in radiological investigations to detect and analyze vascular diseases. Obstructions of the blood flow through a vessel are one of the main interests of physicians, and several methods have been proposed to aid the visual assessment of calcifications on vessel walls. Curved Planar Reformation (CPR) is a wide-spread method that is designed for peripheral arteries which exhibit one dominant direction. To analyze the lumen of arbitrarily oriented vessels, Centerline Reformation (CR) has been proposed. Both methods project the vascular structures into 2D image space in order to reconstruct the vessel lumen. In this paper, we propose Curved Surface Reformation (CSR), a technique that computes the vessel lumen fully in 3D. This offers high-quality interactive visualizations of vessel lumina and does not suffer from problems of earlier methods such as ambiguous visibility cues or premature discretization of centerline data. Our method maintains exact visibility information until the final query of the 3D lumina data. We also present feedback from several domain experts.

    View details for DOI 10.1109/TVCG.2013.215

    View details for Web of Science ID 000325991600091

    View details for PubMedID 24051853

  • Vessel Visualization using Curvicircular Feature Aggregation COMPUTER GRAPHICS FORUM Mistelbauer, G., Morar, A., Varchola, A., Schernthaner, R., Baclija, I., Koechl, A., Kanitsar, A., Bruckner, S., Groeller, E. 2013; 32 (3): 231-240

    View details for DOI 10.1111/cgf.12110

    View details for Web of Science ID 000321184300011

  • ViviSection: Skeleton-based Volume Editing COMPUTER GRAPHICS FORUM Karimov, A., Mistelbauer, G., Schmidt, J., Mindek, P., Schmidt, E., Sharipov, T., Bruckner, S., Groeller, E. 2013; 32 (3): 461-470

    View details for DOI 10.1111/cgf.12133

    View details for Web of Science ID 000321110500010

  • Centerline Reformations of Complex Vascular Structures 5th IEEE Pacific Visualization Symposium Mistelbauer, G., Varchola, A., Bouzari, H., Starinsky, J., Koechl, A., Schernthaner, R., Fleischmann, D., Groeller, M. E., Sramek, M. IEEE COMPUTER SOC. 2012: 233–240
  • Smart Super Views - A Knowledge-Assisted Interface for Medical Visualization Mistelbauer, G., Bouzari, H., Schernthaner, R., Baclija, I., Koechl, A., Bruckner, S., Sramek, M., Groeller, M., Santucci, G., Ward, M. IEEE. 2012: 163-172