NVPHBV Virtual Meeting Series Spring 2021: Anna VilaNova

The NVPHBV: Nederlandse Vereniging voor Patroonherkenning en Beeldverwerking (Dutch Society for Pattern Recognition and Image Processing) is focused on scientific research and practical applications in the field of pattern recognition, image processing, and computer vision. The NVPHBV is the Dutch representative in the International Association for Pattern Recognition (IAPR)

NVPHBV

NVPHBV Virtual Meeting Series Spring 2021: Visual  Analytics for Biomedical Applications

Virtual Meeting - Tuesday, April 6, 202116:00 Opening by Bart ter Haar Romeny, NVPHBV chairman 16:05 &quot;Visual Analytics for Biomedical Applications&quot;, Prof. Anna Vilanova, Eindhoven University of Technology16:45 Q&amp;A with Anna17:00 EndSession and Q&amp;A moderators: Bart ter Haar Romeny &amp; John Schavemaker

AbstractVisual analytics is a branch of visualization that focuses on analytical reasoning facilitated by interaction and visual representations. Visual analytics is an extension to AI methods. It is also a complement to the already existing visualization techniques by the introduction of the concepts of reasoning and AI. Interaction and enhancement of human reasoning and decision making are central. AI has successfully developed models that outperform humans in several tasks. However, this success is limited when it comes to increasing knowledge, and providing new understanding based on new data. The complexity of the human reasoning and consciousness is often needed to generated new insight. The research in my group has focused on visual analytics for data exploration, hypothesis generation and understanding for biomedical applications, such as, virtual colonoscopy, diffusion weighted imaging for brain white-matter and muscle, and 4D blood flow analysis. For this purpose, we developed interactive visualization strategies, including uncertainties and facilitating the analysis of cohort data. Most recently we worked on the concept of progressive visual analytics and the use of dimensionality reduction as an effective VA component for large high-dimensional data visualization. Visual analytics techniques are also a promising approach to open the black-box AI models.

BiographyProf.Dr. Anna Vilanova is full professor in visual analytics since October 2019, at the department of Mathematics and Computer Science, at the Eindhoven University of Technology (TU/e). She is also associated to the Electrical Engineering department within the Signal Processing Systems at TU/e. Previously she was associate professor for 6 years at the Computer Graphics &amp; Visualization Group at EEMCS at the University of Deft, the Netherlands. From 2002 to August 2013, she was Assistant Professor at the Biomedical Image Analysis group of the Biomedical Engineering Department at TU/e.Prof. Vilanova has pioneered research developments in medical visualization. During her PhD on colon unfolding, she presented how to analyze virtual endoscopic images by virtually unfolding the colon with limited distortion, facilitating the analysis and detection of polyps. Later she focused her research on the visualization of complex medical imaging information (i.e., tensor, vector field, multivariate information per voxel). Furthermore, her group was one of the first to work in diffusion weighted/tensor MRI visualization, which allows the in-vivo analysis and visualization of brain connectivity. Similarly, she worked on 4D MRI flow visualization for hemodynamics understanding. A relevant focus point is the inclusion of uncertainty and variability for cohort analysis of complex data in the presentation of the results.Prof. Vilanova has generated novel visual analytics methodology to facilitate the understanding and hypothesis generation by visual exploration, aiding the scientific shift that the big data era is generating. She got remarkable successes in the development of novel dimensionality reduction techniques that address the computational bottleneck and scalability issues that are essential to interactive visual analysis. The developed methodology in the group have made possible the exploration of mass cytometry data in novel ways. Papers in Nature Communications and the Journal of Experimental Medicine describe new findings that were possible due to her team’s visual analytics technology.She has published over 170 peer reviewed publications and has graduated 13 PhDs. The research developed in collaboration with a PhD student won the EuroVis PhD award, the IEEE VGTC 2019 Best Dissertation Award and the Eurographics Dirk Bartz Medical Prize. In 2005, she was awarded an NWO-Veni, a Dutch personal grant, and in 2013 she got a Dutch NWO-Aspasia grant. She is EUROGRAPHICS Fellow since 2019.She is member of the international program committee of several conferences (e.g., IEEE Visualization and EG- IEEE VGTC-EuroVis). She has been chair and editor of relevant conferences and journals in her field of research (e.g., EuroVis 2008, Computer &amp; Graphics, Computer Graphics Forum). She was member of the steering committee of IEEE VGTC EuroVis since 2014 -2018. She is elected member of the EUROGRAPHICS executive committee since 2015 and vice president of EUROGRAPHICS since 2019.

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NVPHBV Virtual Meeting Series Spring 2021: Anna VilaNova

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NVPHBV Virtual Meeting Series Spring 2021: Anna VilaNova

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