Occlusion-free Blood Flow Animation with Wall Thickness Visualization

A Survey of Designs for Combined 2D+3D Visual Representations

We examine visual representations of data that make use of combinations of both 2D and 3D data mappings. Combining 2D and 3D representations is a common technique that allows viewers to understand multiple facets of the data with which they are interacting. While 3D representations focus on the spatial character of the data or the dedicated 3D data mapping, 2D representations often show abstract data properties and take advantage of the unique benefits of mapping to a plane. Many systems have used unique combinations of both types of data mappings effectively. Yet there are no systematic reviews of the methods in linking 2D and 3D representations. We systematically survey the relationships between 2D and 3D visual representations in major visualization publications-IEEE VIS, IEEE TVCG, and EuroVis-from 2012 to 2022. We closely examined 105 articles where 2D and 3D representations are connected visually, interactively, or through animation. These approaches are designed based on their visual environment, the relationships between their visual representations, and their possible layouts. Through our analysis, we introduce a design space as well as provide design guidelines for effectively linking 2D and 3D visual representations.

A Review of Three-Dimensional Medical Image Visualization

Importance. Medical images are essential for modern medicine and an important research subject in visualization. However, medical experts are often not aware of the many advanced three-dimensional (3D) medical image visualization techniques that could increase their capabilities in data analysis and assist the decision-making process for specific medical problems. Our paper provides a review of 3D visualization techniques for medical images, intending to bridge the gap between medical experts and visualization researchers.Highlights. Fundamental visualization techniques are revisited for various medical imaging modalities, from computational tomography to diffusion tensor imaging, featuring techniques that enhance spatial perception, which is critical for medical practices. The state-of-the-art of medical visualization is reviewed based on a procedure-oriented classification of medical problems for studies of individuals and populations. This paper summarizes free software tools for different modalities of medical images designed for various purposes, including visualization, analysis, and segmentation, and it provides respective Internet links.Conclusions. Visualization techniques are a useful tool for medical experts to tackle specific medical problems in their daily work. Our review provides a quick reference to such techniques given the medical problem and modalities of associated medical images. We summarize fundamental techniques and readily available visualization tools to help medical experts to better understand and utilize medical imaging data. This paper could contribute to the joint effort of the medical and visualization communities to advance precision medicine.

Visualization of Human Spine Biomechanics for Spinal Surgery

We propose a visualization application, designed for the exploration of human spine simulation data. Our goal is to support research in biomechanical spine simulation and advance efforts to implement simulation-backed analysis in surgical applications. Biomechanical simulation is a state-of-the-art technique for analyzing load distributions of spinal structures. Through the inclusion of patient-specific data, such simulations may facilitate personalized treatment and customized surgical interventions. Difficulties in spine modelling and simulation can be partly attributed to poor result representation, which may also be a hindrance when introducing such techniques into a clinical environment. Comparisons of measurements across multiple similar anatomical structures and the integration of temporal data make commonly available diagrams and charts insufficient for an intuitive and systematic display of results. Therefore, we facilitate methods such as multiple coordinated views, abstraction and focus and context to display simulation outcomes in a dedicated tool. By linking the result data with patient-specific anatomy, we make relevant parameters tangible for clinicians. Furthermore, we introduce new concepts to show the directions of impact force vectors, which were not accessible before. We integrated our toolset into a spine segmentation and simulation pipeline and evaluated our methods with both surgeons and biomechanical researchers. When comparing our methods against standard representations that are currently in use, we found increases in accuracy and speed in data exploration tasks. in a qualitative review, domain experts deemed the tool highly useful when dealing with simulation result data, which typically combines time-dependent patient movement and the resulting force distributions on spinal structures.

Classification of Blood Flow Patterns in Cerebral Aneurysms

We present a Cerebral Aneurysm Vortex Classification (CAVOCLA) that allows to classify blood flow in cerebral aneurysms. Medical studies assume a strong relation between the progression and rupture of aneurysms and flow patterns. To understand how flow patterns impact the vessel morphology, they are manually classified according to predefined classes. However, manual classifications are time-consuming and exhibit a high inter-observer variability. In contrast, our approach is more objective and faster than manual methods. The classification of integral lines, representing steady or unsteady blood flow, is based on a mapping of the aneurysm surface to a hemisphere by calculating polar-based coordinates. The lines are clustered and for each cluster a representative is calculated. Then, the polar-based coordinates are transformed to the representative as basis for the classification. Classes are based on the flow complexity. The classification results are presented by a detail-on-demand approach using a visual transition from the representative over an enclosing surface to the associated lines. Based on seven representative datasets, we conduct an informal interview with five domain experts to evaluate the system. They confirmed that CAVOCLA allows for a robust classification of intra-aneurysmal flow patterns. The detail-on-demand visualization enables an efficient exploration and interpretation of flow patterns.

Combined Visualization of Vessel Deformation and Hemodynamics in Cerebral Aneurysms

We present the first visualization tool that combines patient-specific hemodynamics with information about the vessel wall deformation and wall thickness in cerebral aneurysms. Such aneurysms bear the risk of rupture, whereas their treatment also carries considerable risks for the patient. For the patient-specific rupture risk evaluation and treatment analysis, both morphological and hemodynamic data have to be investigated. Medical researchers emphasize the importance of analyzing correlations between wall properties such as the wall deformation and thickness, and hemodynamic attributes like the Wall Shear Stress and near-wall flow. Our method uses a linked 2.5D and 3D depiction of the aneurysm together with blood flow information that enables the simultaneous exploration of wall characteristics and hemodynamic attributes during the cardiac cycle. We thus offer medical researchers an effective visual exploration tool for aneurysm treatment risk assessment. The 2.5D view serves as an overview that comprises a projection of the vessel surface to a 2D map, providing an occlusion-free surface visualization combined with a glyph-based depiction of the local wall thickness. The 3D view represents the focus upon which the data exploration takes place. To support the time-dependent parameter exploration and expert collaboration, a camera path is calculated automatically, where the user can place landmarks for further exploration of the properties. We developed a GPU-based implementation of our visualizations with a flexible interactive data exploration mechanism. We designed our techniques in collaboration with domain experts, and provide details about the evaluation.

PelVis: Atlas-based Surgical Planning for Oncological Pelvic Surgery

Due to the intricate relationship between the pelvic organs and vital structures, such as vessels and nerves, pelvic anatomy is often considered to be complex to comprehend. In oncological pelvic surgery, a trade-off has to be made between complete tumor resection and preserving function by preventing damage to the nerves. Damage to the autonomic nerves causes undesirable post-operative side-effects such as fecal and urinal incontinence, as well as sexual dysfunction in up to 80 percent of the cases. Since these autonomic nerves are not visible in pre-operative MRI scans or during surgery, avoiding nerve damage during such a surgical procedure becomes challenging. In this work, we present visualization methods to represent context, target, and risk structures for surgical planning. We employ distance-based and occlusion management techniques in an atlas-based surgical planning tool for oncological pelvic surgery. Patient-specific pre-operative MRI scans are registered to an atlas model that includes nerve information. Through several interactive linked views, the spatial relationships and distances between the organs, tumor and risk zones are visualized to improve understanding, while avoiding occlusion. In this way, the surgeon can examine surgically relevant structures and plan the procedure before going into the operating theater, thus raising awareness of the autonomic nerve zone regions and potentially reducing post-operative complications. Furthermore, we present the results of a domain expert evaluation with surgical oncologists that demonstrates the advantages of our approach.

Visibility Equalizer Cutaway Visualization of Mesoscopic Biological Models

In scientific illustrations and visualization, cutaway views are often employed as an effective technique for occlusion management in densely packed scenes. We propose a novel method for authoring cutaway illustrations of mesoscopic biological models. In contrast to the existing cutaway algorithms, we take advantage of the specific nature of the biological models. These models consist of thousands of instances with a comparably smaller number of different types. Our method constitutes a two stage process. In the first step, clipping objects are placed in the scene, creating a cutaway visualization of the model. During this process, a hierarchical list of stacked bars inform the user about the instance visibility distribution of each individual molecular type in the scene. In the second step, the visibility of each molecular type is fine-tuned through these bars, which at this point act as interactive visibility equalizers. An evaluation of our technique with domain experts confirmed that our equalizer-based approach for visibility specification was valuable and effective for both, scientific and educational purposes.