VCBM 10: Eurographics Workshop on Visual Computing for Biology and Medicine

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Visualizing White Matter Fiber Tracts with Optimally Fitted Curved Dissection Surfaces
(The Eurographics Association, 2010) Schurade, Ralph; Hlawitschka, Mario; Hamann, Bernd; Scheuermann, Gerik; Knösche, Thomas R.; Anwander, Alfred; Dirk Bartz and Charl Botha and Joachim Hornegger and Raghu Machiraju and Alexander Wiebel and Bernhard Preim
bundles in the embedding tissue structures. White matter fiber tractography from diffusion tensor imaging (DTI) is, in general, visualized as 3D lines or tubes together with 2D anatomical MR slices or surfaces. However, determining the exact location of the fiber tracts in their surrounding anatomy is still unsolved. Rendering the embedding anatomy of fiber tracts provides new insight into the exact spatial arrangement of fiber bundles, their spatial relation, and tissue properties surrounding the tracts [SSA*08]. We propose a virtual Klingler dissection method of brain white matter creating curved dissection surfaces locally parallel to user specified fiber bundles. To achieve this effect in computer visualization, we create free-form clipping surfaces that align with the fiber structure of the brain and texture these according to structures they intersect or align with. An optimal view on the naturally embedding curved anatomical structure of the surrounding tissue enables the study of location and course of fiber bundles and the specific relation between different fiber systems in the brain. Indication of the local fiber orientation on the dissected brain surface leads to a representation of both, structural and directional information. The system is demonstrated on a human DTI dataset illustrating the dissection of the sub-insular white matter.
Evaluation of Hippocampal Segmentation Methods for Healthy and Pathological Subjects
(The Eurographics Association, 2010) Bishop, Courtney A.; Jenkinson, Mark; Declerck, Jerome; Merhof, Dorit; Dirk Bartz and Charl Botha and Joachim Hornegger and Raghu Machiraju and Alexander Wiebel and Bernhard Preim
Hippocampal atrophy is a clinical biomarker of Alzheimer's disease (AD) and is implicated in many other neurological and psychiatric diseases. For this reason, there is much interest in the accurate, reproducible delineation of this region of interest (ROI) in structural MR images. Here, both current and novel MR hippocampal segmentation methods are presented and evaluated: Two versions of FMRIB's Integrated Registration and Segmentation Tool (FIRST and FIRSTv2), Freesurfer's Aseg (FS), Classifier Fusion (CF) and a Fast Marching approach (FMClose). Segmentation performance on two clinical datasets is assessed according to three common measures: Dice coefficient, false positive rate (FPR) and false negative rate (FNR). The first clinical dataset contains 9 normal controls (NC) and 8 highly-atrophied AD patients, whilst the second is a collection of 16 NC and 16 bipolar (BP) patients. Results show that CF outperforms all other methods on the BPSA data, whilst FIRST and FIRSTv2 perform best on the CMA data, with average Dice coefficients of 0.81+-0.01, 0.85+-0.00 and 0.85+-0.01, respectively. This work brings to light several strengths and weaknesses of the evaluated hippocampal segmentation methods, of utmost importance for robust and accurate segmentation in the presence of specific and substantial pathology.
Estimation of the Midsagittal Plane for Sideness Determination of Malignant Structures of Head and Neck
(The Eurographics Association, 2010) Rössling, Ivo; Hahn, Peter; Cyrus, Christian; Dornheim, Lars; Dirk Bartz and Charl Botha and Joachim Hornegger and Raghu Machiraju and Alexander Wiebel and Bernhard Preim
Besides other main criterias like size, infiltration and anatomical district, the sideness of tumor and local metastases (i. e., malignant lymph nodes) is very crucial for head and neck tumor assessment. An automatic sideness determination may speed up tumor staging noticeably. Inspired by preliminary work of others we present a modified approach for the estimation of the midsagittal plane based on surface meshes. The suitability of the computed result being used in the course of TNM classification was tested in a case study, in terms of an according automatic determination of the sideness for segmented lymph nodes and tumors.
Model-based Solid Texture Synthesis for Anatomic Volume Illustration
(The Eurographics Association, 2010) Kabul, Ilknur; Merck, Derek; Rosenman, Julian; Pizer, Stephen M.; Dirk Bartz and Charl Botha and Joachim Hornegger and Raghu Machiraju and Alexander Wiebel and Bernhard Preim
Medical illustrations can make powerful use of texture synthesis to convey information about anatomic structures in an attractive, effective and understandable way. Current visualization methods are not capable of conveying detailed information about the orientation, internal structure, and other local properties of the anatomical objects for a particular patient because imaging modalities such as CT or MRI do not capture this information. In this paper, a new anatomical rendering method that utilizes model-based synthesis of 3D textures is proposed in order to distinguish and illustrate different structures inside the model. The goal of our volume illustration approach is to visualize structural information by considering directions and layers in synthesizing high-quality, high-resolution solid textures. Our method uses medial coordinates of 3D models and 2D exemplar textures to generate solid textures that change progressively in orientation and material according to the local orientation and transition information implicit in the anatomic region.Discrete medial 3D anatomical models ("m-reps") provide the orientation field and texture variation maps inside image regions. In our paper, we demonstrate the robustness of our method with a variety of textures applied to different anatomical structures, such as muscles, and mandible.
Graph Averaging as a Means to Compare Multichannel EEG Coherence Networks
(The Eurographics Association, 2010) Crippa, Alessandro; Maurits, Natasha M.; Roerdink, Jos B. T. M.; Dirk Bartz and Charl Botha and Joachim Hornegger and Raghu Machiraju and Alexander Wiebel and Bernhard Preim
A method is proposed for quantifying differences between multichannel EEG coherence networks represented by functional unit (FU) maps. The approach is based on inexact graph matching for attributed relational graphs and graph averaging, adapted to FU maps. The mean of a set of input FU maps is defined in such a way that it not only represents the mean group coherence during a certain task or condition but also to some extent displays individual variations in brain activity. The definition of a mean FU map relies on a graph dissimilarity measure which takes into account both node positions and node or edge attributes. A visualization of the mean FU map is used with a visual representation of the frequency of occurrence of nodes and edges in the input FUs. This makes it possible to investigate which brain regions are more commonly involved in a certain task, by analysing the occurrence of an FU of the mean graph in the input FUs. Furthermore, our method gives the possibility to quantitatively compare individual FU maps by computing their distance to the mean FU map.
Importance-Driven Structure Categorization for 3D Surgery Planning
(The Eurographics Association, 2010) Baer, Alexandra; Kellermann, Kerstin; Preim, Bernhard; Dirk Bartz and Charl Botha and Joachim Hornegger and Raghu Machiraju and Alexander Wiebel and Bernhard Preim
We present an importance-driven categorization approach to automatically gather all currently required structures for the surgery planning process. Therefore, we analyzed common demands for tumor intervention planning and integrated domain knowledge to enable a determination of the relevant structures for various surgical questions. The categorization of structures in focus, focus-relevant and context is defined and initiated by the question. Our method uses the structure's specific meta data and geometric information to determine an importance value for each structure automatically. This importance value encodes the structure's priority for the current question and defines the structure's category. Furthermore, this value can be used to define a structure-specific visual style to generate expressive 3D surgery planning visualizations.
Interactive Real Time Simulation of Cardiac Radio-Frequency Ablation
(The Eurographics Association, 2010) Pernod, Erik; Sermesant, Maxime; Relan, Jatin; Delingette, Herve; Dirk Bartz and Charl Botha and Joachim Hornegger and Raghu Machiraju and Alexander Wiebel and Bernhard Preim
Virtual reality based therapy simulation meets a growing interest from the medical community due to its potential impact for the training of medical residents and the planning of therapies. In this paper, we describe a prototype for rehearsing radio-frequency ablation of the myocardium in the context of cardiac arrhythmia. Our main focus has been on the real-time modeling of electrophysiology which is suitable for representing simple cases of arrhythmia (ectopic focus, ventricular tachycardia). To this end, we use an anisotropic multi-front fast marching method to simulate transmembrane potential propagation in cardiac tissues. The electric propagation is coupled with a pre-recorded beating heart model. Thanks to a 3D user interface, the user can interactively measure the local extracellular potential, pace locally the myocardium or simulate the burning of cardiac tissue as done in radiofrequency ablation interventions. To illustrate this work, we show the simulation of various arrhythmias cases built from patient specific medical images including the right and left ventricles, the fiber orientation and the location of ischemic regions.
Anatomical Volume Visualization with Weighted Distance Fields
(The Eurographics Association, 2010) Kerwin, Thomas; Hittle, Brad; Shen, Han-Wei; Stredney, Don; Wiet, Gregory; Dirk Bartz and Charl Botha and Joachim Hornegger and Raghu Machiraju and Alexander Wiebel and Bernhard Preim
We describe the use of the weighted distance transform (WDT) to enhance applications designed for volume visualization of segmented anatomical datasets. The WDT is presented as a general technique to generate a derived characteristic of a scalar field that can be used in multiple ways during rendering. We obtain real-time interaction with the volume by calculating the WDT on the graphics card. Several examples of this technique as it applies to an application for teaching anatomical structures are detailed, including rendering embedded structures, fuzzy boundaries, outlining, and indirect lighting estimation.
Efficient Globally Optimal Matching of Anatomical Trees of the Liver
(The Eurographics Association, 2010) Laura, Cristina Oyarzun; Drechsler, Klaus; Dirk Bartz and Charl Botha and Joachim Hornegger and Raghu Machiraju and Alexander Wiebel and Bernhard Preim
Many inexact automatic tree matching algorithms are nowadays available. However, they provide matches that are not completely error free. Another option is to use manually matched node-pairs, but this enormously slows down the process. Our contribution to the state of the art is to combine the advantages of both solutions. We enhance the automatic tree matching algorithm designed by Graham et al., so that it is possible to interact with it by previously selecting important matches or by subsequently fixing the provided wrong matches. Thanks to this enhancement the speed of the algorithm is greatly increased. It takes 7.45 seconds for trees up to 192 nodes and less than 1 second if three input matches are provided. In addition to this an in-depth evaluation of the robustness of the algorithm is presented. The results are remarkable. The average of wrong matches varies between 1.17 and 1.4 node-pairs in the worst cases. The rate of correct matches is high.
Adapted Surface Visualization of Cerebral Aneurysms with Embedded Blood Flow Information
(The Eurographics Association, 2010) Gasteiger, Rocco; Neugebauer, Mathias; Kubisch, Christoph; Preim, Bernhard; Dirk Bartz and Charl Botha and Joachim Hornegger and Raghu Machiraju and Alexander Wiebel and Bernhard Preim
Cerebral aneurysms are a vascular dilatation induced by a pathological change of the vessel wall and often require treatment to avoid rupture. Therefore, it is of main interest, to estimate the risk of rupture, to gain a deeper understanding of aneurysm genesis, and to plan an actual intervention, the surface morphology and the internal blood flow characteristics. Visual exploration is primarily used to understand such complex and variable type of data. Since the blood flow data is strongly influenced by the surrounding vessel morphology both have to be visually combined to efficiently support visual exploration. Since the flow is spatially embedded in the surrounding aneurysm surface, occlusion problems have to be tackled. Thereby, a meaningful visual reduction of the aneurysm surface that still provides morphological hints is necessary. We accomplish this by applying an adapted illustrative rendering style to the aneurysm surface. Our contribution lies in the combination and adaption of several rendering styles, which allow us to reduce the problem of occlusion and avoid most of the disadvantages of the traditional semi-transparent surface rendering, like ambiguities in perception of spatial relationships. In interviews with domain experts, we derived visual requirements. Later, we conducted an initial survey with 40 participants (13 medical experts of them), which leads to further improvements of our approach.
Accelerated Diffusion Operators for Enhancing DW-MRI
(The Eurographics Association, 2010) Rodrigues, Paulo; Duits, Remco; Romeny, Bart M. ter Haar; Vilanova, Anna; Dirk Bartz and Charl Botha and Joachim Hornegger and Raghu Machiraju and Alexander Wiebel and Bernhard Preim
the intra-voxel diffusion pattern compared to its simpler predecessor diffusion tensor imaging (DTI). However, HARDI in general produces very noisy diffusion patterns due to the low SNR from the scanners at high b-values. Furthermore, it still exhibits limitations in areas where the diffusion pattern is asymmetrical (bifurcations, splaying fibers, etc.). To overcome these limitations, enhancement and denoising of the data based on context information is a crucial step. In order to achieve it, convolutions are performed in the coupled spatial and angular domain. Therefore the kernels applied become also HARDI data. However, these approaches have high computational complexity of an already complex HARDI data processing. In this work, we present an accelerated framework for HARDI data regularizaton and enhancement. The convolution operators are optimized by: pre-calculating the kernels, analysing kernels shape and utilizing look-up-tables. We provide an increase of speed, compared to previous brute force approaches of simpler kernels. These methods can be used as a preprocessing for tractography and lead to new ways for investigation of brain white matter.
Visual Analysis of Integrated Resting State Functional Brain Connectivity and Anatomy
(The Eurographics Association, 2010) Dixhoorn, Andre F. van; Vissers, Bastijn H.; Ferrarini, Luca; Milles, Julien; Botha, Charl P.; Dirk Bartz and Charl Botha and Joachim Hornegger and Raghu Machiraju and Alexander Wiebel and Bernhard Preim
Resting state functional magnetic resonance imaging (rs-fMRI) is an important modality in the study of the functional architecture of the human brain. The correlation between the resting state fMRI activity traces of different brain regions indicates to what extent they are functionally connected. rs-fMRI data typically consists of a matrix of correlations, also denoted as functional correlations, between regions in the brain. Visualization is required for a good understanding of the data. Several well-known representations have been used to visualize this type of data, including multi-dimensional scaling, spring embedding, scatter plots and network visualization. None of these methods provide the ability to show the functional correlation in relation to the anatomical distance and position of the regions, while preserving the ability to quickly identify outliers in the data. In this paper, a visual analysis application is presented that overcomes this limitation by combining the strengths of the two-dimensional representations with three dimensional network and iso-surfacing visualizations. We show how the application facilitates rs-fMRI connectivity research by means of a case study evaluation.
Dynamic Visualisation of Orbital Fat Deformation using Anatomy-Guided Interaction
(The Eurographics Association, 2010) Schaafsma, Peter J.; Schutte, Sander; Simonsz, Huib J.; Post, Frits H.; Botha, Charl P.; Dirk Bartz and Charl Botha and Joachim Hornegger and Raghu Machiraju and Alexander Wiebel and Bernhard Preim
The human eye is a biomechanical system. Orbital fat plays an important role in the working of this system, but its behaviour during eye movement is not well understood. To give insight into this behaviour, visualisation is a useful tool. This paper presents a complete pipeline for interactive particle-based visualisation and exploration of orbital fat deformation from MRI data. Sensible 3D particle seeding is important in this type of visualisation. We address that problem with a two-step process: Interactive, anatomy-guided slice positioning, and contour-based region of interest specification. Since the deformation calculation is unlikely to be correct everywhere, we derive and visualise an uncertainty measure based on deformed and original MRI data. We also performed a case study evaluation to investigate the benefits of our approach towards orbital fat deformation visualisation.
Staircase-Aware Smoothing of Medical Surface Meshes
(The Eurographics Association, 2010) Moench, Tobias; Adler, Simon; Preim, Bernhard; Dirk Bartz and Charl Botha and Joachim Hornegger and Raghu Machiraju and Alexander Wiebel and Bernhard Preim
The evaluation of spatial relationships between anatomic structures is a major task in surgical planning. Surface models generated from medical image data (intensity, binary) are often used for visualization and 3D measurement of extents and distances between neighboring structures. In applications for intervention or radiation treatment planning, the surface models should exhibit a natural look (referring to smoothness of the surface), but also be accurate. Smoothing algorithms allow to reduce artifacts from mesh generation, but often degrade accuracy. In particular, relevant features may be removed and distances between adjacent structures get changed. Thus, we present a modification to common mesh smoothing algorithms, which allows to focus the smoothing effect directly to previously identified staircase artifacts. This allows to preserve non-artifact features. The approach has been applied to various data to demonstrate the suitability for different anatomical shapes. The results are compared to the ones of standard uniform mesh smoothing algorithms and are evaluated regarding smoothness and accuracy with respect to the application within surgical planning.
Fast and Smooth Interactive Segmentation of Medical Images Using Variational Interpolation
(The Eurographics Association, 2010) Heckel, Frank; Konrad, Olaf; Peitgen, Heinz-Otto; Dirk Bartz and Charl Botha and Joachim Hornegger and Raghu Machiraju and Alexander Wiebel and Bernhard Preim
We present a fast and interactive segmentation method for medical images that allows a smooth reconstruction of an object's surface from a set of user drawn, three-dimensional, planar contours that can be arbitrarily oriented. Our algorithm uses an interpolation based on variational implicit functions. Because variational interpolation is computationally expensive, we show how to speed up the algorithm to achieve an interactive calculation time while preserving the overall segmentation quality. The performance improvements are based on a quality preserving reduction of the number of contour points and a fast voxelization strategy for the resulting implicit function. A huge speedup is achieved by the parallelization of the algorithms, utilizing modern 64-bit multi-core CPUs. Finally, we discuss how to make the interpolation algorithm more robust to selfintersecting and reduced contours.
A General Approach to Model Biomedical Data from 3D Unorganised Point Clouds with Medial Scaffolds
(The Eurographics Association, 2010) Leymarie, Frederic Fol; Chang, Ming-Ching; Imielinska, Celina; Kimia, Benjamin B.; Dirk Bartz and Charl Botha and Joachim Hornegger and Raghu Machiraju and Alexander Wiebel and Bernhard Preim
We present the latest developments in modeling 3D biomedical data via the Medial Scaffold (MS), a 3D acyclic oriented graph representation of the Medial Axis (MA) [LK07, SP08]. TheMS (and associated 3DMA) can be computed as the result of the singularities of a geometric wave propagation simulation. We consider here some of the potential applications of this shape model in the realm of biomedical imaging. We can reconstruct complex object surfaces and make explicit the coarse-scale structures, which are ready-to-use in a number of practical applications, including: morphological measurement for cortex or bone thickness, centerline extraction (curve skeleton) for tracheotomy or colonoscopy, surface partitioning for cortical or anatomical surface classification, as well as registration and matching of shapes of tumors or carpal bones. TheMS permits to automatically and efficiently map an unorganised point cloud, i.e., simple 3D coordinates of point samples, to a coherent surface set and associated approximate MA. The derivedMS is used to further recover significant medium and large scale features, such as surface ridges and main axial symmetries. The radius field of theMS provides an intuitive definition for morphological measurements, while the graph structure made explicit by theMS is useful for shape registration and matching applications.
Guided Visualization of Ultrasound Image Sequences
(The Eurographics Association, 2010) Angelelli, Paolo; Viola, Ivan; Nylund, Kim; Gilja, Odd Helge; Hauser, Helwig; Dirk Bartz and Charl Botha and Joachim Hornegger and Raghu Machiraju and Alexander Wiebel and Bernhard Preim
Ultrasonography allows informative and expressive real time examinations of patients. Findings are usually reported as printouts, screen shots and video sequences. However, in certain scenarios, the amount of imaged ultrasound data is considerable or it is challenging to detect the anatomical features of interest. Post-examination access to the information present in the data is, therefore, cumbersome. The examiner must, in fact, review entire video sequences or risk to lose relevant information by reducing the examination to single screen shot and printouts. In this paper we propose a novel post-processing pipeline for guided visual exploration of ultrasound video sequences, to allow easier and richer exploration and analysis of the data. We demonstrate the usefulness of this approach by applying it to a liver examination case, showing easier and quicker ultrasound image selection and data exploration.

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