Kolloquiumszyklus - previous dates

Multiscale modeling and visualization of cellular environments is an important topic from a scientific as well as educational perspective. It plays an important role in analyzing and understanding metabolic processes, structural molecular complexes or the targeting of drugs.
The CELLmicrocosmos project combines different information layers for multiple purposes:
At the molecular level, the MembraneEditor is used by many projects to model heterogeneous membranes as a base for molecular simulations and analyses [SDGS11]. Showing small parallels to cellVIEW [LAPV15], the CellExplorer is a software tool which can be used to visualize and explore cell environments at the mesoscopic level. Combined with the PathwayIntegration, cytological networks can be localized and integrated into these cell environments [KoGS16, SKSH10]. In the recent years we developed a number of new cytological visualization approaches which can be explored on multiple scales: from the local computer, to web browsers, to mobile phones and Head-­‐mounted displays, and to large-­‐scale virtual environments like the CAVE2 [FNTT13, KoGS16, SBHG14, SHKC16, SWXC15]. In this context we are currently working with the CeBiTec Bielefeld on the visualization of a Chlamydomas rheinhardtii cell.

[FNTT13] FEBRETTI, Alessandro; NISHIMOTO, Arthur; THIGPEN, Terrance; TALANDIS, Jonas; LONG, Lance; PIRTLE, J. D.; PETERKA, Tom; VERLO, Alan; et al.:
CAVE2:  a hybrid reality environment for immersive simulation and information analysis. In: IS&T/SPIE lectronic Imaging : International Society for Optics and Photonics,  2013, pp. 864903-­‐864903–12 

[KoGS16] KOVANCI, Gökhan; GHAFFAR, Mehmood; SOMMER, Björn: Web-­‐based hybrid-­‐ dimensional Visualization and Exploration of Cytological Localization Scenarios. In: Journal of  Integrative Bioinformatics 13 (2016), no. 4, p. 298

[LAPV15] LE MUZIC, Mathieu; AUTIN, Ludovic; PARULEK, Julius; VIOLA, Ivan: cellVIEW: a tool for illustrative and multi-­‐scale rendering of large biomolecular datasets. In: Proceedings of the Eurographics Workshop on Visual Computing for Biology and Medicine : Eurographics  Association, 2015, pp. 61–70

[SBHG14] SOMMER, Björn; BENDER, Christian; HOPPE,   Tobias; GAMROTH, Christian;  JELONEK, Lukas: Stereoscopic cell visualization: from   mesoscopic to molecular scale. In: Electronic Imaging, Proceedings of Stereoscopic Displays   and Applications  XXVIII 23 (2014), no. 1, pp. 011007-­‐1-­‐011007-­‐10

[SDGS11] SOMMER, B.; DINGERSEN, T.; GAMROTH, C.;SCHNEIDER, S. E.; RUBERT, S.;  KRÜGER,  J.; DIETZ, K. J.: CELLmicrocosmos 2.2 MembraneEditor: a modular interactive
shape-­‐based  software  approach to solve heterogeneous Membrane Packing Problems. In: Journal of Chemical Information and Modeling 5 (2011), no. 51, pp. 1165–1182

[SHKC16] SOMMER, Björn; HAMACHER, Andreas; KALUZA, Owen; CZAUDERNA, Tobias;
KLAPPERSTÜCK, Matthias; BIERE, Niklas; CIVICO, Marco; THOMAS, Bruce; et al.: Stereoscopic Space Map – Semi-­‐immersive Configuration of 3D-­‐stereoscopic Tours
in Multi-­‐display Environments. In: Electronic Imaging, Proceedings of Stereoscopic Displays and Applications XXVII 2016 (2016), no. 5, pp. 1–9

[SKSH10] SOMMER, Björn; KÜNSEMÖLLER, Jörn; SAND, Norbert; HUSEMANN, Arne; RUMMING, Madis;  KORMEIER, Benjamin:  CELLmicrocosmos 4.1: an interactive approach to  integrating spatially localized metabolic networks into a virtual 3D cell environment. In: FRED, Ana; FILIPE, Joaquim; GAMBOA, Hugo (eds.): BIOSTEC 2010,  2010,pp. 90–95 

[SWXC15] SOMMER, Björn; WANG, Stephen Jia; XU, Lifeng; CHEN, Ming; SCHREIBER, Falk: Hybrid-­‐Dimensional Visualization and Interaction -­‐ Integrating 2D and 3D Visualization with Semi-­‐Immersive Navigation Techniques. In: Big  Data Visual Analytics (BDVA), 2015 : IEEE, 2015, pp. 1–8   

Modeling and rendering complex materials is among the central concerns
in Computer Graphics, and the Entertainment Industry is always eager to
feature photorealistic and attractive emulations of our everyday life.
However, accurate modeling and rendering of materials with complex
mesostructure (for instance, porous materials) has not received as much
attention as other topics in the literature. In this presentation we
will review some proposals in modeling and rendering this kind of
materials.

As a modeling case, bread turns out to be a structurally complex
material, for which the eye is in particular very sensitive in spotting
improper models, making adequate bread modeling a difficult task. We
developed an accurate computational bread baking model that allows to
faithfully represent the geometrical mesostructure and the appearance of
bread through its making process. This is achieved by a careful
simulation of the conditions during proving and baking to get a
realistically looking result. Some of the generative steps in the
process can be easily adapted to model other kinds of porous materials
(f.e., stones or sponges).

Regarding rendering, a remarkable property of porous materials is how
water or other liquids in their surface alter significantly their BRDFs,
which in turn determines subtle or overt changes in their visual
features. For this reason, rendering materials that change their
appearance when wet continues to be challenging. We are developing a
principled and comprehensive technique to model and render the changes
in appearance of absorbent materials under humidity conditions. This
includes a method to solve the interaction between the fluid and the
solid model, the fluid diffusion within the solid porous media, and a
physically based rendering model that adequately simulates the light
transfer behavior under these conditions. Additional features of this
model are: geometry easy to represent and to interact with, and
reasonable rendering times using off-the-shelf GPUs.

Short Bio:

Claudio Delrieux is BS in Electric Engineering, and PhD in Computer Science. He is currently full professor and PI at the Electric and Computer Engineering Department in the Universidad Nacional del Sur (Argentina), fellow of the National Council of Science and Technology of Argentina (CONICET), and Chair of the Imaging Sciences Laboratory. His current interests are Image and Video Processing, Computer Graphics, Scientific Visualization, and Artificial Intelligence. He is author of more than 45 refereed journal papers, and more than 100 refereed international conference papers. Supervisor of 10 PhD theses (currently another 10) and 5 MSc theses (3 ongoing). PI of 3 ongoing research projects, and 5 ongoing applied research and technology transfer agreements.

Abstract

In the era of Big Data, visual analytics becomes an important tool for scientific research, engineering design, and critical decision making. The design of a visual analytics solution must take into account the data characteristics, the media used, the users, the tasks to support,
etc., each of which presents some unique requirements and challenges.
These challenges demands new technical approaches and design considerations.  I will discuss them using research results that my group has produced as examples.

Short Bio

Kwan-Liu Ma is a professor of computer science and the chair of the Graduate Group in Computer Science (GGCS) at the University of California-Davis, where he directs VIDI Labs and UC Davis Center of Excellence for Visualization. His research spans the fields of visualization, computer graphics, high-performance computing, and user interface design. Professor Ma received his PhD in computer science from the University of Utah in 1993. During 1993-1999, he was with ICASE/NASA Langley Research Center as a research scientist. He joined UC Davis in 1999. Professor Ma received numerous recognitions for his research contributions such as the NSF Presidential Early-Career Research Award (PECASE) in 2000, the UC Davis College of Engineering's Outstanding Mid-Career Research Faculty Award in 2007, and the 2013 IEEE VGTC Visualization Technical Achievement Award. He was elected an IEEE Fellow in 2012.

Abstract

What if we could create and manipulate data directly inside visualizations? How would the visual representation of data affect what we can do to it? How could interaction allow us to express our ideas as evolving data? Building on well-known systems and principles of interactive visualization design, I will offer a glimpse of visualization as an expressive workspace for observing and interpreting the world interactively, and present recent progress on building the foundations of such a workspace.

Short Bio

Chris Weaver is an Associate Professor in the School of Computer Science at the University of Oklahoma. He has a B.S. in Chemistry and Math from Michigan State University, an M.S. and Ph.D. in Computer Science from the University of Wisconsin-Madison, and spent 3 years as a post-doc with the GeoVISTA Center at Penn State University. In 2013 he served as Conference Chair of the IEEE Conference on Information Visualization. His research is supported in part by a 2014 NSF CAREER award and focuses on bringing people, data, and visualization together, with a special interest in supporting scholarship and learning in the humanities.

I will review in this talk the application of information theory to aesthetics. Information theory, developed by Claude Shannon, provides powerful tools to study the information content of any kind of data. We will use these tools to study the low level information content of Van Gogh paintings, and show that our results match well with the analysis by art critics.

Structural concepts are important on many levels for molecular biology. In this talk, I will additionally underline the importance of visualization methods for structural research, while also juxtaposing the formation visualization concept as an engineering field with artistic representations as a field of fine arts.

As a first example, I will define a phylogenetic structure based on a simulation framework for (molecular) sequence evolution. On the one side, I will discuss scientific applications: for example for selecting and filtering non-coding RNA gene-candidates. From the perspective of information visualization, tools that allows for the interactive exploration of candidates and their genomic regions have been validated and evaluated. On the other side, I will discuss some of the points and questions, which arise about the incompleteness of any structure’s description and visualization.

As a second example , I will present our most recently development of a chemical descriptor system for small molecules, the Shannon entropy descriptor.

This talk will show how data visualization can be used to provide public visitor venues, such as museums, science centres and zoos with unique interactive learning experiences. The talk will focus on the on how to bridge the distance from basic research to implementation in the galleries discuss issues such as interaction design and storytelling.  The talk will take its starting point in volumetric medical data captured with the latest modalities. By combining visualization techniques with technologies such as interactive multi-touch tables and intuitive user interfaces, visitors can conduct guided browsing of large volumetric image data. The visitors then themselves become the explorers of the normally invisible interior of unique artefacts and subjects. Demonstrations of the Inside Explorer software will be used as examples. The talk will then discuss the use of large scale immersive environments, such as dome theatres, for science communication. The unique technical and design challenges in producing content for both playback interactive demonstrations will be discussed. Examples will be taken from shows produced at the Norrköping Visualization Center. A live demo of the new NASA funded OpenSpace software initiative will conclude the talk.

Biology has become accessible to an understanding of processes that span from atom to organism.  As such we now have the opportunity to model a spatio-temporal picture of living systems at the molecular level.  In our recent work we attempt to create, interact with, and communicate physical representations of complex molecular environments. I will discuss the challenges and demonstrate three levels of interaction with complex molecular environments: 1) human perceptual and cognitive interaction with complex structural information; 2) interaction and integration of multiple data sources to construct cellular environments at the molecular level; and 3) interaction of software tools that can bridge the disparate disciplines needed to explore, analyze and communicate a holistic molecular view of living systems.In order to increase our understanding and interaction with complex molecular structural information we have combined two evolving computer technologies, 3D printing and augmented reality1. We create custom tangible molecular models and track their manipulation with real-time video, superimposing text and graphics onto the models to enhance their information content and to drive interactive computation. We have developed automated technologies to construct the crowded molecular environment of living cells from structural information at multiple scales as well as bioinformatics information on levels of protein expression and other data2.  We can populate cytoplasm, membranes, and organelles within the same structural volume to generate cellular environments that synthesize our current knowledge of such systems. Examples of applications of this technology will be discussed. The communication of complex structural information requires extensive scientific knowledge as well as expertise in creating clear visualizations.  We have developed a method of combining scientific modeling environments with professional grade 3D modeling and animation programs such as Maya, Cinema4D and Blender3 , as well as the Unity Game engine.  This gives both scientists and professional illustrators access to the best tools to create and communicate the science and the art of the molecular cell.

1Gillet, A., Sanner, M., Stoffler, D., Olson, A.J. (2005) Tangible interfaces for structural molecular biology. Structure:13:483-491.

2Johnson GT, Autin L, Al-Alusi M, Goodsell DS, Sanner MF, Olson AJ. cellPACK: a virtual mesoscope to model and visualize structural systems biology. Nat Methods. 2015 Jan;12(1):85-91.

3 Autin, L., Johnson, G., Hake, J., Olson, A.J., Sanner, M.F. (2012) uPy: A Ubiquitous CG Python API with Biological-Modeling Applications. Computer Graphics & Applications 32(5):50-61.

Visualization is a powerful exploration and storytelling tool for large complex, multidimensional data. The design of a visualization solution must take into account the data characteristics, the media used, and the purpose of the visualization, each of which presents some unique challenges. These challenges suggest new topics for visualization research. I will discuss some of these topics and present related research results produced by my group.

Biography:

Kwan-Liu Ma is a professor of computer science and the chair of the Graduate Group in Computer Science (GGCS) at the University of California-Davis, where he directs VIDI Labs and UC Davis Center of Excellence for Visualization. His research spans the fields of visualization, computer graphics, high-performance computing, and user interface design. Professor Ma received his PhD in computer science from the University of Utah in 1993. During 1993-1999, he was with ICASE/NASA Langley Research Center as a research scientist. He joined UC Davis in 1999. Professor Ma received numerous recognitions for his research contributions such as the NSF Presidential Early-Career Research Award (PECASE) in 2000, the UC Davis College of Engineering's Outstanding Mid-Career Research Faculty Award in 2007, and the 2013 IEEE VGTC Visualization Technical Achievement Award. He was elected an IEEE Fellow in 2012.

The primary goal of visual data exploration tools is to enable the discovery of new insights. To justify and reproduce insights, the discovery process needs to be documented and communicated. A common approach to documenting and presenting findings is to capture visualizations as images or videos. Images, however, are insufficient for telling the story of a visual discovery, as they lack full provenance information and context. Videos are difficult to produce and edit, particularly due to the non-linear nature of the exploratory process. Most importantly, however, neither approach provides the opportunity to return to any point in the exploration in order to review the state of the visualization in detail or to conduct additional analyses. In this talk, I will introduce CLUE (Capture, Label, Understand, Explain), a model that tightly integrates data exploration and presentation of discoveries. Based on provenance data captured during the exploration process, users can extract key steps, add annotations, and author 'Vistories', visual stories based on the history of the exploration. These Vistories can be shared for others to view, but also to retrace and extend the original analysis. I will also discuss how the CLUE approach can be integrated into visualization tools. Finally, I will also demonstrate the general applicability of the model in multiple usage scenarios, including an example from molecular biology that illustrates how Vistories could be used in scientific journals.

I'll describe VoroCrust, the first algorithm for simultaneous surface reconstruction and volumetric Voronoi meshing. By surface reconstruction, I mean that weighted sample points are created on a smooth manifold, and we are tasked with building a mesh (triangulation) containing those points that approximates the surface. By Voronoi meshing, I mean that we create Voronoi cells that are well-shaped polytopal decompositions of the spaces inside and outside the manifold. By "simultaneous", I mean that the surface mesh is the interface of the two volume meshes.

VoroCrust meshes are distinguished from the usual approach of clipping Voronoi cells by the manifold, which results in many extra surface vertices beyond the original samples, and may result in non-planar, non-convex, or even non-star-shaped cells.

The VoroCrust algorithm is similar to the famous "power crust." Unlike the power crust, our output Voronoi cells are unweighted and have good aspect ratio. Moreover, there is complete freedom of how to mesh the volume far from the surface. Most of the reconstructed surface is composed of Delaunay triangles with small circumcircle radius, and all samples are vertices. In the presence of slivers, the reconstruction lies inside the sliver, interpolating between its upper and lower pair of bounding triangles, and introducing Steiner vertices.

To understand how the immune system works, one needs to have a clear picture of its cellular compositon and the cells’ corresponding properties and functionality. Mass cytometry is a novel technique to determine the properties of single-cells with unprecedented detail. This amount of detail allows for much finer differentiation but also comes at the cost of more complex analysis. In this work, we present Cytosplore, implementing an interactive workflow to analyze mass cytometry data in an integrated system, providing multiple linked views, showing different levels of detail and enabling the rapid definition of known and unknown cell types. Cytosplore handles millions of cells, each represented as a high-dimensional data point, facilitates hypothesis generation and confirmation, and provides a significant speed up of the current workflow.

This presentation will first briefly discuss the relevance of using medical image analysis and visualization in health care, and thereafter present a number of example clinical applications of image analysis and visualization in the domains of cardiovascular, neurological and oncological disease. The focus will be on using magnetic resonance imaging (MRI).

Despite the enormous amount of medical imaging research and development performed in the last decades, only a very limited number of applications are currently routinely used in clinical practice. The road from idea to a clinically adopted and widely used application will be reviewed in order to create insight into the many steps to be taken to develop and introduce truly meaningful innovations.

Online service providers, such as Twitter, Amazon, Google, and Wikipedia, generate huge volumes of user behavior data daily, in which valuable patterns and correlations of user behaviors are hidden. For companies, effective analysis of the behavior data allows them to learn more about their customers on an unprecedented scale to improve customer relations and develop social media marketing strategies. For governments, effective tracking of the behavior data allows them to detect and predict critical events to make proper decisions in a timely manner. However, analysis of the behavior data is challenging due to the enormous amount of data and the heterogeneity of information. In my talk, I will discuss the challenges of the research on visual behavior analytics, and then give some examples of applying interactive visualization techniques to making sense of the behavior data. 

We introduce the design and implementation of Proscene-3, a highly customizable open source framework for interactive environments comprising three layers: a low-level component providing a set of virtual events which represent all sorts of input sources and the means to bind user-defined actions to them; a mid-level component, implementing a feature-rich set of widely-used motion actions allowing picking & manipulation of objects, including the scene viewpoint; and, a high-level library, exposing those features to the Processing language.

In this talk, I give an overview of perceptually motivated techniques for the visualization of medical image data. These techniques include physics-based lighting and illustrative rendering that incorporate spatial depth and shape cues. In addition, I discuss evaluations that were conducted in order to study the perceptual effects of these visualization techniques as compared to conventional techniques. These evaluations assessed depth and shape perception with depth judgment, orientation matching, and related tasks. This overview of existing techniques and their evaluation serves as a basis for defining the evaluation process of medical visualizations.

Molecular dynamics simulations allow scientists to run virtual experiments that can even reproduce the interactions in molecular systems with previously unknown behavior. That is, these simulations provide us with a “Computational Microscope” that enables studying the dynamic behavior of proteins and other biomolecules down to individual atoms. Interactive visualization is an essential part of this Computational Microscope, since it allows domain experts to explore the results of their simulations. Direct visualizations of the data using established molecular models show the dynamics of the simulated molecules. While such direct visualizations can already reveal many interesting processes, interactive analysis can further enhance the exploratory data analysis with the results of feature extractions. In my talk, I will discuss algorithms for direct molecular visualization as well as several examples of interactive visual analysis methods for biomolecular simulation data, including real-time cavity detection algorithms and comparative visualizations. I will also present actual use cases where interactive visual analysis led to the discovery of unexpected phenomena in the simulated molecular systems.

Mapping from data tables to visual abstraction is a crucial step in the visualization pipeline. It often determines if a visualization will be successful or not.

Basic visual structures: points, lines, shapes, and color are combined into more complex visual representations. We explain standard representations for 1D, 2D, 3d, and nD data, such as, histogram, box-plot, pie-chart, scatter-plot, or parallel coordinates, for example.
Further, we provide guidelines how to use them and explain how not use certain visual structures.

Problems of using 2D or 3D structures to depict 1D data, or the problem of line-width illusion are also explained. The students should gain basic understanding of the importance of the visual-mapping step in the visualization pipeline, and they should be able to choose right visualization, and to recognize misleading visualization.

Most of the cellular processes are driven by protein activities. For example, chemical energy is generated by ATP synthases, replication is driven by PCNA clamp, transcription is regulated by transcription factors, DNA is structured by histones and SMC proteins etc. Most of the cellular proteins, however, exist and function as multi-subunit complexes (such as ATP pump, replisome, enhanceosome, nucleosome etc.). Such complexes are assembled thru multiple protein interactions, which determine their architecture, function and dynamics.

In this lecture, several protein complexes will be shown in a bottom up way i.e. starting from single protein/subunit interactions to complexes and further to large molecular assemblies. I will review state-of-the-art experimental methods for protein/complex analysis and their output formats, including animations of molecular machines. Use of visualization techniques for protein complex animations and their potential for description of dynamic cellular processes will be discussed.

Within this talk I will cover our recent work in the area of molecular visualization. Two techniques will be presented, which have been developed with the goal to improve the spatial comprehension of complex molecular structures. First, coverage-based opacity estimation is discussed as a technique to achieve Depth of Field (DoF) effects when visualizing molecular structures. The proposed algorithm is an object-based approach which eliminates many of the shortcomings of state-of-the-art image-based DoF algorithms. Based on observations derived from a physically-correct reference renderer, coverage-based opacity estimation exploits semi-transparency to simulate the blur inherent to DoF effects. It achieves high quality DoF effects, by augmenting each atom with a semi-transparent shell, which has a radius proportional to the distance from the focal plane of the camera. Thus, each shell represents an additional coverage area whose opacity varies radially, based on our observations derived from the results of multi-sampling DoF algorithms. Second, I will discuss the integration of diffuse illumination effects into molecular visualization. While current molecular visualization techniques utilize ambient occlusion as a global illumination approximation in order to improve spatial comprehension, interreflections are also known to improve the spatial comprehension of complex geometric structures. To realize these interreflections in real-time, an analytic approach is exploited for capturing interreflections of molecular structures. By exploiting the knowledge of the underlying space filling representations, the required parameters can be reduced and symbolic regression can be applied to obtain an analytical expression for interreflections. I will discuss how to obtain the data required for the symbolic regression analysis, and how to exploit the analytic solution to enhance interactive molecular visualizations. For both presented techniques, high quality results will be shown, which a re visually comparable to those of state-of-the-art offline renderers.

3D printing is considered a disruptive technology with potentially tremendous socioeconomic impact. In recent years, additive manufacturing technologies have made significant progress in terms of both sophistication and price; they have advanced to a point where devices now feature high-resolution, full-color, and multi-material printing. Nonetheless, they remain of limited use, given the lack of efficient algorithms and intuitive tools that can be used to design and model 3D-printable content.

My vision is to unleash the full potential of 3D printing technology with the help of computational methods. In our research, we are working to invent and develop new computational techniques for intuitively designing virtual 3D models and bringing them to the real world. Given the digital nature of the process, three factors play a central role: computational models and efficient representations that facilitate intuitive design, accurate and fast simulation techniques, and intuitive authoring tools for physically realizable objects and materials.

In this talk, I will present several projects that demonstrate our recent efforts in working toward this goal, structured according to basic object properties, and the lessons learned from working over several years with various 3D printers.

This talk presents several optimization approaches to customizing and designing the traveling guide maps. The idea behind our approach is to formulate design criteria commonly employed by illustrators as mathematical constraints first and then optimizing the cost function in order to fully enhance the readability of the map layout. We consider two design strategies for this purpose. The first one is for route handling, and the second one is for label placement. To visually guide users’ attention, we try to emphasize the user specified route in the first design, which is accomplished by introducing linear programming(LP) optimization and mixed-integer programming(MIP) technique. As for the second design, we employ genetic algorithm(GA) and again MIP in order to maximally placing thumbnail photographs close to their corresponding stations on the metro maps. Several design examples are also presented to demonstrate the feasibility of our prototype system together with user studies on how users are satisfied with the formulated design criteria.

Recent advances in scanning, modeling, rendering, and hardware make it possible to generate nearphotorealistic images of moderately complex scenes at interactive rates. One of the next grand challenges in computer graphics and visualization is to model vibrant, dynamic scenes of realworld complexity, such as urban spaces. The problem of modeling virtual cityscapes offers a diverse set of opportunities for innovations and provides enabling technologies of societal interests, including energy use, transportation mechanisms, economic sustainability, education and entertainment. Some of the key research issues include interactive simulation of large-scale crowds, realistic modeling of complex traffic flows, efficient motion synthesis of plausible pedestrian behaviors and natural phenomena. At least one to two orders of magnitude performance improvement in hardware will be needed. New algorithms and software systems that can exploit such computing power must be developed.

In this talk, I will survey some of recent efforts on addressing the problem of modeling, simulating, and directing virtual agents in complex dynamic environments. In particular, I will present several complementary approaches for representing movement of multiple virtual entities, including both crowds and traffic, in urban scenes and city highways. I will further highlight the design of scalable algorithms for these problems by taking advantages of parallelism available on emerging commodity hardware, such as GPUs and many-core processors. These methods can be applied to interactive crowd simulation, motion synthesis, and coordination of multiple autonomous agents in computer games and virtual environment systems. I will conclude by discussing our experiences and some future research directions on incorporating sound effects and natural phenomena.

Magnetic Resonance Imaging (MRI) is a primary tool for clinical investigation of the brain and fetal organs. High resolution imaging with volumetric coverage using stacks of slices or true three dimensional (3D) methods is widely available and provides rich data for image analysis. However such detailed volumetric data generally takes several minutes to acquire and requires the subject to remain still or move only small distances during acquisition. Fetal organ imaging introduces a number of additional challenges. Maternal breathing may move the fetus and the fetus itself can and does spontaneously move during imaging. These movements are unpredictable and may be large, particularly involving substantial head and body rotations. Motion correction methods have revolutionized MRI of the fetus  by reconstructing a high-resolution 3D volume of  fetal organs from such motion corrupted stacks of 2D slices. Such reconstructions are valuable for both clinical and research applications. However, reconstruction is computationally expensive and can only be performed off line. Information about the accuracy of the scan and potential uncertainties is unknown or not considered in the clinical practice.

In this talk I will discuss the fundamentals of fetal MRI reconstruction and it's parallelization and hardware acceleration for a future on-line application during the scan. Furthermore, I am looking forward to a discussion about potential application of novel visualization techniques to communicate varying uncertainties of the reconstruction to examining radiologists and scientists.