I’m an Associate Professor in Medical Visualization (tenure track position funded by the Trond Mohn Foundation), with a background in computer science and as a radiographer. I am also affiliated to the Mohn Medical Imaging and Visualization (MMIV) centre as a senior researcher and part of the leadership team. Currently, I am researching novel interactive visualization approaches for improved exploration, analysis, and communication of multimodal medical imaging data. The focus of our team in this context is on multi-parametric MR acquisitions.
Teaching:
- Continuously INF219, INF319 Project in Visualization
- Fall semester 2020: INF219 Project in Visualization: new style involving real clients and seminar lectures
- Spring Semester 2019: INF101 Object-oriented Programming
- Fall Semester 2017/2018: INF358 Seminar in Visualization
This page only displays publications I have authored in my current affiliation. For a full overview, please check my Google Scholar profile. For more information, please check my personal website.
Publications
2021
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[Bibtex] @inproceedings{Rijken-2021-Illegible,
title = {Illegible Semantics: Exploring the Design Space of Metal Logos},
author = {Gerrit J. Rijken and Rene Cutura and Frank Heyen and Michael Sedlmair and Michael Correll and Jason Dykes and Noeska Smit},
year = 2021,
booktitle = {Proceedings of the {alt.VIS} workshop at {IEEE VIS}},
eprint = {2109.01688},
archiveprefix = {arXiv},
primaryclass = {cs.HC},
pdf = {pdfs/Rijken-2021-Illegible.pdf},
thumbnails = {images/Rijken-2021-Illegible.png},
images = {images/Rijken-2021-Illegible.png},
abstract = {The logos of metal bands can be by turns gaudy, uncouth, or nearly illegible. Yet, these logos work: they communicate sophisticated notions of genre and emotional affect. In this paper we use the design considerations of metal logos to explore the space of ``illegible semantics'': the ways that text can communicate information at the cost of readability, which is not always the most important objective. In this work, drawing on formative visualization theory, professional design expertise, and empirical assessments of a corpus of metal band logos, we describe a design space of metal logos and present a tool through which logo characteristics can be explored through visualization. We investigate ways in which logo designers imbue their text with meaning and consider opportunities and implications for visualization more widely.},
youtube = "https://youtu.be/BZOdIhU-mrA",
}![[DOI]](https://vis.uib.no/wp-content/plugins/papercite/img/external.png){kind=small}
[Bibtex] @inproceedings{Smit-2021-DataKnitualization,
title = {Data Knitualization: An Exploration of Knitting as a Visualization Medium},
author = {Noeska Smit},
year = 2021,
booktitle = {Proceedings of the {alt.VIS} workshop at {IEEE VIS}},
doi = {10.31219/osf.io/xahj9},
pdf = {pdfs/Smit-2021-DataKnitualization.pdf},
thumbnails = {images/Smit-2021-DataKnitualization.jpg},
images = {images/Smit-2021-DataKnitualization.jpg},
abstract = {While data visualization can be achieved in many media, from hand-drawn on paper to 3D printed via data physicalization, the ancient craft of knitting is not often considered as a visualization medium. With this work, I explore hand knitting as a potential data visualization medium based on my personal experience as a knitter and visualization researcher.},
youtube = "https://youtu.be/K3D-M7jzbMs",
}@article{Gillmann-2021-Viewpoints,
author = {C. Gillmann and N. N. Smit and E. Groller and B. Preim and A. Vilanova and T. Wischgoll},
journal = {IEEE Computer Graphics and Applications},
title = {Ten Open Challenges in Medical Visualization},
year = {2021},
volume = {41},
number = {05},
issn = {1558-1756},
pages = {7-15},
keywords = {deep learning;uncertainty;data visualization;medical services;standardization;artificial intelligence;biomedical imaging},
doi = {10.1109/MCG.2021.3094858},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
pdf = {pdfs/Gillmann-2021-Viewpoints.pdf},
thumbnails = {images/Gillmann-2021-Viewpoints.png},
images = {images/Gillmann-2021-Viewpoints.png},
project = {ttmedvis},
abstract = {The medical domain has been an inspiring application area in visualization research for many years already, but many open challenges remain. The driving forces of medical visualization research have been strengthened by novel developments, for example, in deep learning, the advent of affordable VR technology, and the need to provide medical visualizations for broader audiences. At IEEE VIS 2020, we hosted an Application Spotlight session to highlight recent medical visualization research topics. With this article, we provide the visualization community with ten such open challenges, primarily focused on challenges related to the visualization of medical imaging data. We first describe the unique nature of medical data in terms of data preparation, access, and standardization. Subsequently, we cover open visualization research challenges related to uncertainty, multimodal and multiscale approaches, and evaluation. Finally, we emphasize challenges related to users focusing on explainable AI, immersive visualization, P4 medicine, and narrative visualization.}
}@inproceedings{Hushagen-2021-VCBM,
title = {The Role of Depth Perception in {XR} from a Neuroscience Perspective: A Primer and Survey},
author = {Hushagen, Vetle and Tresselt, Gustav C. and Smit, Noeska N. and Specht, Karsten},
year = 2021,
booktitle = {Eurographics Workshop on Visual Computing for Biology and Medicine},
publisher = {The Eurographics Association},
doi = {10.2312/vcbm.20211344},
isbn = {978-3-03868-140-3},
issn = {2070-5786},
url = {https://diglib.eg.org/handle/10.2312/vcbm20211344},
pdf = {pdfs/Hushagen-2021-VCBM.pdf},
thumbnails = {images/Hushagen-2021-VCBM.png},
images = {images/Hushagen-2021-VCBM.png},
project = {ttmedvis},
abstract = {Augmented and virtual reality (XR) are potentially powerful tools for enhancing the efficiency of interactive visualization of complex data in biology and medicine. The benefits of visualization of digital objects in XR mainly arise from enhanced depth perception due to the stereoscopic nature of XR head mounted devices. With the added depth dimension, XR is in a prime position to convey complex information and support tasks where 3D information is important. In order to inform the development of novel XR applications in the biology and medicine domain, we present a survey which reviews the neuroscientific basis underlying the immersive features of XR. To make this literature more accessible to the visualization community, we first describe the basics of the visual system, highlighting how visual features are combined to objects
and processed in higher cortical areas with a special focus on depth vision. Based on state of the art findings in neuroscience literature related to depth perception, we provide several recommendations for developers and designers. Our aim is to aid development of XR applications and strengthen development of tools aimed at molecular visualization, medical education, and surgery, as well as inspire new application areas.}
}@inproceedings{Sugathan-2021-VCBM,
title = {Interactive Multimodal Imaging Visualization for Multiple Sclerosis Lesion Analysis},
author = {Sugathan, Sherin and Bartsch, Hauke and Riemer, Frank and Gr{\"u}ner, Renate and Lawonn, Kai and Smit, Noeska N},
year = 2021,
booktitle = {Eurographics Workshop on Visual Computing for Biology and Medicine},
publisher = {The Eurographics Association},
doi = {10.2312/vcbm.20211346},
isbn = {978-3-03868-140-3},
issn = {2070-5786},
url = {https://diglib.eg.org/handle/10.2312/vcbm20211346},
pdf = {pdfs/Sugathan-2021-VCBM.pdf},
thumbnails = {images/Sugathan-2021-VCBM.png},
images = {images/Sugathan-2021-VCBM.png},
project = {ttmedvis},
abstract = {Multiple Sclerosis (MS) is a brain disease that is diagnosed and monitored extensively through MRI scans. One of the criteria is the appearance of so-called brain lesions. The lesions show up on MRI scans as regions with elevated or reduced contrast compared to the surrounding healthy tissue.
Understanding the complex interplay of contrast, location and shape in images from multiple modalities from 2D MRI slices is challenging.
Advanced visualization of appearance- and location-related features of lesions would help researchers in defining better disease characterization through MS research.
Since a permanent cure is not possible in MS and medication-based disease modification is a common treatment path, providing better visualizations would strengthen research which investigates the effect of white matter lesions. Here we present an advanced visualization solution that supports analysis from multiple imaging modalities acquired in a clinical routine examination. The solution holds potential for enabling researchers to have a more intuitive perception of lesion features. As an example for enhancing the analytic possibilities, we demonstrate the benefits of lesion projection using both Diffusion Tensor Imaging (DTI) and gradient-based techniques. This approach enables users to assess brain structures across individuals as the atlas-based analysis provides 3D anchoring and labeling of regions across a series of brain scans from the same participant and across different participants. The projections on the brain surface also enable researchers to conduct detailed studies on the relationship between cognitive disabilities and location of lesions. This allows researchers to correlate lesions to Brodmann areas and related brain functions.
We realize the solutions in a prototype application that supports both DTI and structural data. A qualitative evaluation demonstrates that our approach supports MS researchers by providing new opportunities for MS research.}
}@InProceedings{Garrison-2021-EPP,
author = {Laura Garrison and Monique Meuschke and Jennifer Fairman and Noeska Smit and Bernhard Preim and Stefan Bruckner},
title = {An Exploration of Practice and Preferences for the Visual Communication of Biomedical Processes},
booktitle = {Proceedings of VCBM},
year = {2021},
pages = {},
doi = {},
abstract = {The visual communication of biomedical processes draws from diverse techniques in both visualization and biomedical illustration. However, matching these techniques to their intended audience often relies on practice-based heuristics or narrow-scope evaluations. We present an exploratory study of the criteria that audiences use when evaluating a biomedical process visualization targeted for communication. Designed over a series of expert interviews and focus groups, our study focuses on common communication scenarios of five well-known biomedical processes and their standard visual representations. We framed these scenarios in a survey with participant expertise spanning from minimal to expert knowledge of a given topic. Our results show frequent overlap in abstraction preferences between expert and non-expert audiences, with similar prioritization of clarity and the ability of an asset to meet a given communication objective. We also found that some illustrative conventions are not as clear as we thought, e.g., glows have broadly ambiguous meaning, while other approaches were unexpectedly preferred, e.g., biomedical illustrations in place of data-driven visualizations. Our findings suggest numerous opportunities for the continued convergence of visualization and biomedical illustration techniques for targeted visualization design.},
note = {Accepted for publication, to be presented at VCBM 2021},
project = {VIDI,ttmedvis},
pdf = {pdfs/Garrison-2021-EPP.pdf},
thumbnails = {images/Garrison-2021-EPP.png},
images = {images/Garrison-2021-EPP.jpg},
url = {https://github.com/lauragarrison87/Biomedical_Process_Vis},
keywords = {biomedical illustration, visual communication, survey},
}@incollection{Smit-2021-COMULIS,
author = {Smit, Noeska and Bühler, Katja and Vilanova, Anna and Falk, Martin},
title = {Visualisation for correlative multimodal imaging},
booktitle = {Imaging Modalities for Biological and Preclinical Research: A Compendium, Volume 2},
publisher = {IOP Publishing},
year = {2021},
series = {2053-2563},
type = {Book Chapter},
pages = {III.4.e-1 to III.4.e-10},
abstract = {In this chapter, we describe several approaches to interactive imaging data visualization in general, highlight several strategies for visualizing correlative multimodal imaging data, and provide examples and practical recommendations.},
url = {http://dx.doi.org/10.1088/978-0-7503-3747-2ch28},
doi = {10.1088/978-0-7503-3747-2ch28},
isbn = {978-0-7503-3747-2},
thumbnails = "images/Smit-2021-COMULIS.PNG",
images = "images/Smit-2021-COMULIS.PNG",
project = "ttmedvis",
abstract = {The field of visualisation deals with finding appropriate visual representations of data so people can effectively carry out tasks related to data exploration, analysis, or presentation using the power of the human visual perceptual system. In the context of biomedical imaging data, interactive visualisation techniques can be employed, for example, to visually explore data, as image processing quality assurance, or in publications to communicate findings. When dealing with correlative imaging, challenges arise in how to effectively convey the information from multiple sources. In particular, the information density leads to the need for a critical reflection on the visual design with respect to which parts of the data are important to show and at what level of importance they should be visualised. In this chapter, we describe several approaches to interactive imaging data visualisation in general, highlight several strategies for visualising correlative multimodal imaging data, and provide examples and practical recommendations.}
}2020
[Bibtex] @article{Garrison-2020-IVE,
author = {Garrison, Laura and Va\v{s}\'{i}\v{c}ek, Jakub and Craven, Alex R. and Gr\"{u}ner, Renate and Smit, Noeska and Bruckner, Stefan},
title = {Interactive Visual Exploration of Metabolite Ratios in MR Spectroscopy Studies},
journal = {Computers \& Graphics},
volume = {92},
pages = {1--12},
keywords = {medical visualization, magnetic resonance spectroscopy data, information visualization, user-centered design},
doi = {10.1016/j.cag.2020.08.001},
abstract = {Magnetic resonance spectroscopy (MRS) is an advanced biochemical technique used to identify metabolic compounds in living tissue. While its sensitivity and specificity to chemical imbalances render it a valuable tool in clinical assessment, the results from this modality are abstract and difficult to interpret. With this design study we characterized and explored the tasks and requirements for evaluating these data from the perspective of a MRS research specialist. Our resulting tool, SpectraMosaic, links with upstream spectroscopy quantification software to provide a means for precise interactive visual analysis of metabolites with both single- and multi-peak spectral signatures. Using a layered visual approach, SpectraMosaic allows researchers to analyze any permutation of metabolites in ratio form for an entire cohort, or by sample region, individual, acquisition date, or brain activity status at the time of acquisition. A case study with three MRS researchers demonstrates the utility of our approach in rapid and iterative spectral data analysis.},
year = {2020},
pdf = "pdfs/Garrison-2020-IVE.pdf",
thumbnails = "images/Garrison-2020-IVE.png",
images = "images/Garrison-2020-IVE.jpg",
project = "VIDI",
git = "https://github.com/mmiv-center/spectramosaic-public",
}