Context-aware mesh smoothing for biomedical applications

Moench, Tobias; Gasteiger, Rocco; Janiga, Gábor; Theisel, Holger; Preim, Bernhard

doi:10.1016/j.cag.2011.04.011

Cited by 29 publications

(10 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Visually obvious artifacts occurring during the imaging process were manually corrected in all cases (BLENDER 2.68A, Amsterdam, The Netherlands). To achieve a high surface quality, the segmentation results were transformed into discrete triangular meshes (approximately 0.1 mm resolution) and smoothed afterward using a Taubin smoothing algorithm [29,30]. A neuroradiologist reviewed the modified geometries afterward to check the plausibility of the reconstructed shapes.…”

Section: Vascular Reconstructionmentioning

confidence: 99%

The Computational Fluid Dynamics Rupture Challenge 2013—Phase II: Variability of Hemodynamic Simulations in Two Intracranial Aneurysms

Berg

Roloff

Beuing

et al. 2015

Journal of Biomechanical Engineering

View full text Add to dashboard Cite

With the increased availability of computational resources, the past decade has seen a rise in the use of computational fluid dynamics (CFD) for medical applications. There has been an increase in the application of CFD to attempt to predict the rupture of intracranial aneurysms, however, while many hemodynamic parameters can be obtained from these computations, to date, no consistent methodology for the prediction of the rupture has been identified. One particular challenge to CFD is that many factors contribute to its accuracy; the mesh resolution and spatial/temporal discretization can alone contribute to a variation in accuracy. This failure to identify the importance of these factors and identify a methodology for the prediction of ruptures has limited the acceptance of CFD among physicians for rupture prediction. The International CFD Rupture Challenge 2013 seeks to comment on the sensitivity of these various CFD assumptions to predict the rupture by undertaking a comparison of the rupture and blood-flow predictions from a wide range of independent participants utilizing a range of CFD approaches. Twenty-six groups from 15 countries took part in the challenge. Participants were provided with surface models of two intracranial aneurysms and asked to carry out the corresponding hemodynamics simulations, free to choose their own mesh, solver, and temporal discretization. They were requested to submit velocity and pressure predictions along the centerline and on specified planes. The first phase of the challenge, described in a separate paper, was aimed at predicting which of the two aneurysms had previously ruptured and where the rupture site was located. The second phase, described in this paper, aims to assess the variability of the solutions and the sensitivity to the modeling assumptions. Participants were free to choose boundary conditions in the first phase, whereas they were prescribed in the second phase but all other CFD modeling parameters were not prescribed. In order to compare the computational results of one representative group with experimental results, steady-flow measurements using particle image velocimetry (PIV) were carried out in a silicone model of one of the provided aneurysms. Approximately 80% of the participating groups generated similar results. Both velocity and pressure computations were in good agreement with each other for cycle-averaged and peak-systolic predictions. Most apparent "outliers" (results that stand out of the collective) were observed to have underestimated velocity levels compared to the majority of solutions, but nevertheless identified comparable flow structures. In only two cases, the results deviate by over 35% from the mean solution of all the participants. Results of steady CFD simulations of the representative group and PIV experiments were in good agreement. The study demonstrated that while a range of numerical schemes, mesh resolution, and solvers was used, similar flow predictions were observed in the majority of cases. To further validate the computati...

show abstract

Section: Vascular Reconstructionmentioning

confidence: 99%

The Computational Fluid Dynamics Rupture Challenge 2013—Phase II: Variability of Hemodynamic Simulations in Two Intracranial Aneurysms

Berg

Roloff

Beuing

et al. 2015

Journal of Biomechanical Engineering

View full text Add to dashboard Cite

show abstract

“…Afterwards, visually obvious artifacts that occurred during the imaging process were corrected manually (Blender 2.68a, Amsterdam, The Netherlands), especially in areas where the vessel and the aneurysm were melted. Finally, Taubin-smoothing on the discrete surface mesh ensured a more realistic representation (Mönch et al, 2011;Neugebauer et al, 2013). In order to check the plausibility of the reconstructed shape, the treating neuroradiologist reviewed the virtual geometry.…”

Section: Vascular Reconstructionmentioning

confidence: 99%

An automatic CFD-based flow diverter optimization principle for patient-specific intracranial aneurysms

Janiga

Daróczy

Berg

et al. 2015

Journal of Biomechanics

View full text Add to dashboard Cite

“…Besides, using more effective segmentation techniques, or enforcing denoising operation [2] before segmentation (which raises the risk of features removal and the change of relevant properties of the anatomical structures) can also reduce noise. However, this additional effort is usually not recommended, since data with higher resolution increases the computational time and the storage stress in clinical routine [3]. These artifacts can also be processed at the mesh generation stage.…”

Section: Introductionmentioning

confidence: 98%

“…Recently, some researchers attempted to solve the artifacts on medical surface by carefully selecting existing filters (e.g., in [17] [18]) or by adapting some of them (e.g., in [19] [3]). However, these efforts are still based on the traditional smoothing framework, which cannot completely avoid the aforementioned disadvantages.…”

Section: Introductionmentioning

confidence: 99%

Effective mesh smoothing for haptic rendering in medical applications

Zhu

Wei

Zhu

et al. 2014

2014 4th IEEE International Conference on Information Science and Technology

View full text Add to dashboard Cite

Mesh models can be extracted from medical imaging data. However some methods (e.g., CT) may suffer from severe artifacts (e.g., staircases, noises) in current clinical routine. As a consequence, haptic systems, when using these influenced mesh models, will become unstable. To tackle this problem, in this paper we propose an effective medical-oriented smoothing algorithm focusing on haptic rendering. Our algorithm mainly consists of two stages, namely vertex re-sampling and surface fitting. The first stage is adopted to eliminate staircases while the second can obtain the underlying surface by least square fitting method. Experiments on various medical imaging data present the efficacy of our methodology, which can achieve higher quality results than previous approaches regarding both surface smoothness and surface accuracy. And the final results on haptic applications further show this proposed technique is suitable for medical surgery simulations.

show abstract

Context-aware mesh smoothing for biomedical applications

Cited by 29 publications

References 14 publications

The Computational Fluid Dynamics Rupture Challenge 2013—Phase II: Variability of Hemodynamic Simulations in Two Intracranial Aneurysms

The Computational Fluid Dynamics Rupture Challenge 2013—Phase II: Variability of Hemodynamic Simulations in Two Intracranial Aneurysms

An automatic CFD-based flow diverter optimization principle for patient-specific intracranial aneurysms

Effective mesh smoothing for haptic rendering in medical applications

Contact Info

Product

Resources

About