2025
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@inproceedings{zhang2025stories,
author = {Zhang, Ke Er Amy and Garrison, Laura},
title = {Modern snapshots in the crafting of a medical illustration},
booktitle = {Proceedings of CHI '25 Workshop "How do design stories work? Exploring narrative forms of knowledge in HCI"},
year = {2025},
numpages = {3},
abstract = {The time-honored practice of medical illustration and visualization, has, like nearly all other disciplines, seen changes in its tooling and development pipeline in step with technological and societal developments. At its core, however, medical visualization remains a discipline focused on telling stories about biology and medicine. The story we tell in this work assumes a more distant vantage point to tell a story about the biomedical storytellers themselves. Our story peers over the shoulders of two medical illustrators in the middle of a project to illustrate a procedure in one of the small blood vessels around the heart, and through the medium of an online chat explores the dialogue, tensions, and goals of such projects in the digital age. We adopt the two-column format of the CHI template, as it is more reminiscent of the width of our usual messaging windows while working. The second part of our submission reflects on these tensions and modes of storytelling from an HCI and Visualization-situated perspective.},
pdf = {pdfs/zhang2025stories.pdf},
images = {images/zhang2025stories.png},
thumbnails = {images/zhang2025stories.png},
project = {VIDI}
}
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@article{vandenbossche2025open,
title = {The Open Anatomy Explorer--a journey towards accessible open-source 3D learning environments},
author = {Vandenbossche, Vicky and Van Kenhove, Michiel and Smit, Noeska and Willaert, Wouter and De Turck, Filip and Volckaert, Bruno and Valcke, Martin and Audenaert, Emmanuel},
year = 2025,
journal = {Journal of Visual Communication in Medicine},
publisher = {Taylor \& Francis},
pages = {1--12},
doi = {10.1080/17453054.2024.2446764},
url = {https://www.tandfonline.com/doi/full/10.1080/17453054.2024.2446764},
abstract = {Anatomy learning has traditionally relied on drawings, plastic models, and cadaver dissections/prosections to help students understand the three-dimensional (3D) relationships within the human body. However, the landscape of anatomy education has been transformed with the introduction of digital media. In this light, the Open Anatomy Explorer (OPANEX) was developed. It includes two user interfaces (UI): one for students and one for administrators. The administrator UI offers features such as uploading and labelling of 3D models, and customizing 3D settings. Additionally, the OPANEX facilitates content sharing between institutes through its import-export functionality. To evaluate the integration of OPANEX within the existing array of learning resources, a survey was conducted as part of the osteology course at Ghent University, Belgium. The survey aimed to investigate the frequency of use of five learning resources, attitudes towards 3D environments, and the OPANEX user experience. Analysis revealed that the OPANEX was the most frequently used resource. Students’ attitudes towards 3D learning environments further supported this preference. Feedback on the OPANEX user experience indicated various reasons for its popularity, including the quality of the models, regional annotations, and customized learning content. In conclusion, the outcomes underscore the educational value of the OPANEX, reflecting students’ positive attitudes towards 3D environments in anatomy education.},
images = {images/vandenbossche2025open.png},
thumbnails = {images/vandenbossche2025open.png},
pdf = {pdfs/vandenbossche2025open.pdf}
}
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@article{wagner2025mri,
title = {MRI delta radiomics during chemoradiotherapy for prognostication in locally advanced cervical cancer},
author = {Wagner-Larsen, Kari S and Lura, Njål and Gulati, Ankush and Ryste, Stian and Hodneland, Erlend and Fasmer, Kristine E and Woie, Kathrine and Bertelsen, Bjørn I and Salvesen, Øyvind and Halle, Mari K and Smit, Noeska and Krakstad, Camilla and Haldorsen, Ingfrid S},
year = 2025,
journal = {BMC cancer},
volume = 25,
pages = 122,
doi = {10.1186/s12885-025-13509-1},
url = {https://bmccancer.biomedcentral.com/articles/10.1186/s12885-025-13509-1},
abstract = {Effective diagnostic tools for prompt identification of high-risk locally advanced cervical cancer (LACC) patients are needed to facilitate early, individualized treatment. The aim of this work was to assess temporal changes in tumor radiomics (delta radiomics) from T2-weighted imaging (T2WI) during concurrent chemoradiotherapy (CCRT) in LACC patients, and their association with progression-free survival (PFS). Furthermore, to develop, validate, and compare delta- and pretreatment radiomic signatures for prognostic modeling.},
images = {images/wagner2025mri.png},
thumbnails = {images/wagner2025mri.png},
pdf = {pdfs/wagner2025mri.pdf}
}
2024
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@article{splechtna2024interactive,
title={Interactive design-of-experiments: optimizing a cooling system},
author={Splechtna, Rainer and Behravan, Majid and Jelovic, Mario and Gracanin, Denis and Hauser, Helwig and Matkovic, Kre{\v{s}}imir},
journal={IEEE Transactions on Visualization and Computer Graphics},
year={2024},
publisher={IEEE},
doi = {10.1109/TVCG.2024.3456356},
url = {https://doi.org/10.1109/TVCG.2024.3456356},
images = {images/splechtna2024cooling.png},
thumbnails = {images/splechtna2024cooling.png},
pdf = {pdfs/splechtna2024cooling.pdf},
abstract = {The optimization of cooling systems is important in many cases, for example for cabin and battery cooling in electric cars. Such an optimization is governed by multiple, conflicting objectives and it is performed across a multi-dimensional parameter space.The extent of the parameter space, the complexity of the non-linear model of the system,as well as the time needed per simulation run and factors that are not modeled in the simulation necessitate an iterative, semi-automatic approach. We present an interactive visual optimization approach, where the user works with a p-h diagram to steer an iterative, guided optimization process. A deep learning (DL) model provides estimates for parameters, given a target characterization of the system, while numerical simulation is used to compute system characteristics for an ensemble of parameter sets. Since the DL model only serves as an approximation of the inverse of the cooling system and since target characteristics can be chosen according to different, competing objectives, an iterative optimization process is realized, developing multiple sets of intermediate solutions, which are visually related to each other.The standard p-h diagram, integrated interactively in this approach, is complemented by a dual, also interactive visual representation of additional expressive measures representing the system characteristics. We show how the known four-points semantic of the p-h diagram meaningfully transfers to the dual data representation.When evaluating this approach in the automotive domain, we found that our solution helped with the overall comprehension of the cooling system and that it lead to a faster convergence during optimization.}
}
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@article{pokojna2024language,
title={The Language of Infographics: Toward Understanding Conceptual Metaphor Use in Scientific Storytelling},
author={Pokojn{\'a}, Hana and Isenberg, Tobias and Bruckner, Stefan and Kozl{\'i}kov{\'a}, Barbora and Garrison, Laura},
journal={IEEE Transactions on Visualization and Computer Graphics},
year={2024},
month={Oct},
publisher={IEEE},
abstract={We apply an approach from cognitive linguistics by mapping Conceptual Metaphor Theory (CMT) to the visualization domain to address patterns of visual conceptual metaphors that are often used in science infographics. Metaphors play an essential part in visual communication and are frequently employed to explain complex concepts. However, their use is often based on intuition, rather than following a formal process. At present, we lack tools and language for understanding and describing metaphor use in visualization to the extent where taxonomy and grammar could guide the creation of visual components, e.g., infographics. Our classification of the visual conceptual mappings within scientific representations is based on the breakdown of visual components in existing scientific infographics. We demonstrate the development of this mapping through a detailed analysis of data collected from four domains (biomedicine, climate, space, and anthropology) that represent a diverse range of visual conceptual metaphors used in the visual communication of science. This work allows us to identify patterns of visual conceptual metaphor use within the domains, resolve ambiguities about why specific conceptual metaphors are used, and develop a better overall understanding of visual metaphor use in scientific infographics. Our analysis shows that ontological and orientational conceptual metaphors are the most widely applied to translate complex scientific concepts. To support our findings we developed a visual exploratory tool based on the collected database that places the individual infographics on a spatio-temporal scale and illustrates the breakdown of visual conceptual metaphors.},
pdf = {pdfs/garrisonVIS24.pdf},
images = {images/garrisonVIS24.png},
thumbnails = {images/garrisonVIS24thumb.png},
project = {VIDI},
git={https://osf.io/8xrjm/}
}
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@inproceedings{zimanVCBM2024mobaDash,
booktitle = {Eurographics Workshop on Visual Computing for Biology and Medicine},
editor = {Garrison, Laura and Jönsson, Daniel},
title = {{The MoBa Pregnancy and Child Development Dashboard: A Design Study}},
author = {Ziman, Roxanne and Budich, Beatrice and Vaudel, Marc and Garrison, Laura},
year = {2024},
month = {September},
publisher = {The Eurographics Association},
ISSN = {2070-5786},
ISBN = {978-3-03868-244-8},
DOI = {10.2312/vcbm.20241194},
abstract = {Visual analytics dashboards enable exploration of complex medical and genetic data to uncover underlying patterns and possible relationships between conditions and outcomes. In this interdisciplinary design study, we present a characterization of the domain and expert tasks for the exploratory analysis for a rare maternal disease in the context of the longitudinal Norwegian Mother, Father, and Child (MoBa) Cohort Study. We furthermore present a novel prototype dashboard, developed through an iterative design process and using the Python-based Streamlit App [TTK18] and Vega-Altair [VGH*18] visualization library, to allow domain experts (e.g., bioinformaticians, clinicians, statisticians) to explore possible correlations between women's health during pregnancy and child development outcomes. In conclusion, we reflect on several challenges and research opportunities for not only furthering this approach, but in visualization more broadly for large, complex, and sensitive patient datasets to support clinical research.},
pdf = {pdfs/zimanVCBM24.pdf},
images = {images/zimanVCBM24.png},
thumbnails = {images/zimanVCBM24thumb.png},
project = {VIDI},
git={https://osf.io/u6kdm/}
}