exhibition

As observed by journalist Shelley Esaak, artists have long used the human capacity to recognize patterns. Already 20,000 years ago, Palaeolithic artisans painted a beautiful pride of lions in the Lascaux Cave. In 1910, Gustav Klimt created ‘The Tree Of Life’, showcasing a golden template of enchanting branches. Another 50 years later, Andy Warhol famously silkscreened a repeated image of Marilyn Monroe in bright and contrasting colours. Reflecting on this continuous use of patterns, Esaak writes: “The ability to recognize patterns is a baseline skill of humans and identifying patterns is a practice that tends to have a soothing psychological effect on the viewer”. The other way around, the viewer tends to have an eery feeling whenever they see a pattern is broken. According to anthropologist Brigitte Jordan, patternality represents “a deep instinct, a drive, a need to impose order on the world so as to make it usable and survivable”. In this regard, pattern recognition is a phenomenon that comes naturally to us. It is an automatic, cognitive tool that helps us to make sense of the world.
As Professor in Visual Analytics, Anna Vilanova builds on the human visual system not only to understand our surroundings, but also to make sense of data. Indeed, large data collections may give us little understanding of what is going on, but properly visualising that data can help to detect patterns, trends, connections and outliers. To this end, Anna develops visualisation tools and techniques that enable people to “obtain insights into data via interactive computer graphics”.
Anna’s interest in visualization is particularly centred around biomedical applications. Here, a clear and perhaps signature example of such an application is provided by Anna’s work on ‘Diffusion Weighted Imaging’ (DWI). DWI is a form of magnetic resonance imaging that scans the white matter in the brain - tissue that is responsible for connecting different areas of the brain. Among others, these scans can help to better interpret brain diseases, such as multiple sclerosis and dementia. Unfortunately, the original images emerging from the scans offer little guidance to the medics involved. Images may contain noise, show irrelevant details, and be overall distorted as well. This can hamper well-informed and effective decision-making on the side of the neurosurgeon. Medics, therefore, need visualisation techniques that can help them make better sense of the images. In this regard, Anna uses algorithms to better reconstruct white matter. She draws a comparison with anatomy books, which often “use illustrations rather than photographs to convey information”.
The latter dictum returns in other projects as well. Among others, Anna worked on the development of illustrative visualization tools to “interactively explore the 4D blood-flow data and depict the essential blood-flow characteristics”, helping physicians to get a better understanding of the cardiovascular system. Recently, Anna has claimed that visual analytics could also be a major approach to “open the black-box AI models” – to visualize to other scientists how machine-learning operates and how it may be of use to them in their respective fields.
Anna was awarded an NWO-Veni personal grant in 2005 and received an NWO-Aspasia in 2013. Since 2015 and 2021 respectively, Anna has been elected member of the EUROGRAPHICS executive committee and the IEEE VIS steering committee. In addition, Anna is member of the international program committee of several conferences, such as IEEE Visualization and EG- IEEE VGTC-EuroVis. Given its biomedical focus, Anna’s work is important, and it would not be too much of a stretch to claim that Anna creates life-saving images. Interestingly, Anna does not fully rely on the power of computers. The visualisations that she creates serve the human eye – be it that of a neurosurgeon or a physician. Divided by time, then, the Lascaux paintings and Anna’s own images ultimately boil down to the same thing: an appreciation of the human ability to recognize patterns.