Refine
Year of publication
Document Type
- In Proceedings (152)
- Article (131)
- ZIB-Report (32)
- Book chapter (15)
- Other (14)
- In Collection (9)
- Book (3)
- Poster (3)
Keywords
- DVR (2)
- 3D neural network (1)
- Cultural Heritage (1)
- DNA (1)
- Dense connectome (1)
- GPU acceleration (1)
- Gaussian Process (1)
- HCI (1)
- Hierarchical (1)
- Interaction Techniques (1)
- Kendall (1)
- Kiosk application (1)
- Longitudinal (1)
- Medical image segmentation (1)
- Optimal design of computer experiments (1)
- Picking (1)
- Picture/Image Generation, Display algorithms, Three-Dimensional Graphics and Realism, Raytracing (1)
- Procrustes analysis (1)
- RNA (1)
- Reconstruction (1)
- Shape Space (1)
- Sparse kernels (1)
- Surfaces (1)
- Volume Rendering (1)
- atomic radii (1)
- blue-noise (1)
- brushing & linking (1)
- cavity analysis (1)
- computational geometry (1)
- digitally reconstructed radiographs (1)
- direct volume rendering (1)
- dislocation, diffraction contrast, scanning transmission electron microscopy, stereoscopy, visualization (1)
- finite element meshes (1)
- iPad (1)
- image registration (1)
- interaction (1)
- interactive rendering (1)
- mesh deformation (1)
- molecular dynamics (1)
- multi-modal, intergrated data analysis, topology (1)
- picking (1)
- point set optimization (1)
- pointing (1)
- ray casting (1)
- ribonucleic acids (1)
- secondary & tertiary structures (1)
- shape space, shape trajectories, geodesic regression, longitudinal analysis, osteoarthritis (1)
- statistical shape and intensity models (1)
- triangulation (1)
- unfolding, papyri, computed tomography (1)
- virtual anatomy (1)
- volume rendering (1)
Institute
- Visual and Data-centric Computing (359) (remove)
Connectomics is a branch of neuroscience that attempts to create a connectome, i.e., a complete map of the neuronal system and all connections between neuronal structures. This representation can be used to understand how functional brain states emerge from their underlying anatomical structures and how dysfunction and neuronal diseases arise. We review the current state-of-the-art of visualization and image processing techniques in the field of connectomics and describe a number of challenges. After a brief summary of the biological background and an overview of relevant imaging modalities, we review current techniques to extract connectivity information from image data at macro-, meso- and microscales. We also discuss data integration and neural network modeling, as well as the visualization, analysis and comparison of brain networks.
Visualization
(2014)
In this report we review and structure the branch of molecular visualization that is concerned with the visual analysis of cavities in macromolecular protein structures. First the necessary background, the domain terminology, and the goals of analytical reasoning are introduced. Based on a comprehensive collection of relevant research works, we present a novel classification for cavity detection approaches and structure them into four distinct classes: grid-based, Voronoi-based, surface-based, and probe-based methods. The subclasses are then formed by their combinations. We match these approaches with corresponding visualization technologies starting with direct 3D visualization, followed with non-spatial visualization techniques that for example abstract the interactions between structures into a relational graph, straighten the cavity of interest to see its profile in one view, or aggregate the time sequence into a single contour plot. We also discuss the current state of methods for the visual analysis of cavities in dynamic data such as molecular dynamics simulations. Finally, we give an overview of the most common tools that are actively developed and used in the structural biology and biochemistry research. Our report is concluded by an outlook on future challenges in the field.