Eric Mörth

PhD Student

Multimodal Medical Visualization

 Team Smit

I am a PhD student of Multimodal Medical Visualization in Bergen. My PhD is a collaboration between the Mohm Medical Imaging and Visualization Center (MMIV) and the University of Bergen. My PhD is funded by my Supervisor Noeska Smit (Trond Mohn Stiftelse)

My main focus is the research in new and innovative ways to visualize and explore medical data, e.g. MRI data to enable doctors to have a better view at their data. My last projects resulted in successful publications in the field of medical visualization. My two successful conducted master studies in Medical Informatics from the Medical Unviersity of Vienna and Biomedical Engineering from the Technical University of Vienna prepare me well for the challenges I face during my PhD studies. Furthermore, I was able to gather more than 5 years of experience in software development in various companies in Austria.

In my free time I love photography, videography, travelling and to ride and build bycicles.



    [PDF] [DOI] [Bibtex]
    doi = {10.1007/s11695-021-05763-6},
    year = {2021},
    month = nov,
    publisher = {Springer Science and Business Media {LLC}},
    author = {Hannes Beiglb\"{o}ck and Eric M\"{o}rth and Berthold Reichardt and Tanja Stamm and Bianca Itariu and J\"{u}rgen Harreiter and Miriam Hufgard-Leitner and Paul Fellinger and Jakob Eichelter and Gerhard Prager and Alexander Kautzky and Alexandra Kautzky-Willer and Peter Wolf and Michael Krebs},
    title = {Sex-Specific Differences in Mortality of Patients with a History of Bariatric Surgery: a Nation-Wide Population-Based Study},
    journal = {Obesity Surgery},
    abstract = {Bariatric surgery reduces mortality in patients with severe obesity and is predominantly performed in women.
    Therefore, an analysis of sex-specific differences after bariatric surgery in a population-based dataset from Austria was
    performed. The focus was on deceased patients after bariatric surgery.
    The Austrian health insurance funds cover about 98% of the Austrian population. Medical health
    claims data of all Austrians who underwent bariatric surgery from 01/2010 to 12/2018 were analyzed. In total, 19,901 patients
    with 107,806 observed years postoperative were eligible for this analysis. Comorbidities based on International Classification
    of Diseases (ICD)-codes and drug intake documented by Anatomical Therapeutical Chemical (ATC)-codes were analyzed
    in patients deceased and grouped according to clinically relevant obesity-associated comorbidities: diabetes mellitus (DM),
    cardiovascular disease (CV), psychiatric disorder (PSY), and malignancy (M).
    In total, 367 deaths were observed (1.8%) within the observation period from 01/2010 to 04/2020. The overall
    mortality rate was 0.34% per year of observation and significantly higher in men compared to women (0.64 vs. 0.24%;
    p < 0.001(Chi-squared)). Moreover, the 30-day mortality was 0.19% and sixfold higher in men compared to women (0.48
    vs. 0.08%; p < 0.001). CV (82%) and PSY (55%) were the most common comorbidities in deceased patients with no sex-
    specific differences. Diabetes (38%) was more common in men (43 vs. 33%; p = 0.034), whereas malignant diseases (36%)
    were more frequent in women (30 vs. 41%; p = 0.025).
    After bariatric surgery, short-term mortality as well as long-term mortality was higher in men compared to
    women. In deceased patients, diabetes was more common in men, whereas malignant diseases were more common in women.},
    pdf = {pdfs/Beiglboeck2021_Article_Sex-SpecificDifferencesInMorta.pdf},
    thumbnails = {images/2021-Moerth-Diabetes-thumb.png},
    images = {images/2021-Moerth-Diabetes.png},
    keywords = {Bariatric surgery, Sex differences, Mortality, Population-based registry analysis, Comorbidities, Healthcare, research},


    [PDF] [DOI] [YT] [Bibtex]
    author = {M\"{o}rth, E. and Wagner-Larsen, K. and Hodneland, E. and Krakstad, C. and Haldorsen, I. S. and Bruckner, S. and Smit, N. N.},
    title = {RadEx: Integrated Visual Exploration of Multiparametric Studies for Radiomic Tumor Profiling},
    journal = {Computer Graphics Forum},
    volume = {39},
    number = {7},
    year = {2020},
    pages = {611--622},
    abstract = {Better understanding of the complex processes driving tumor growth and metastases is critical for developing targeted treatment strategies in cancer. Radiomics extracts large amounts of features from medical images which enables radiomic tumor profiling in combination with clinical markers. However, analyzing complex imaging data in combination with clinical data is not trivial and supporting tools aiding in these exploratory analyses are presently missing. In this paper, we present an approach that aims to enable the analysis of multiparametric medical imaging data in combination with numerical, ordinal, and categorical clinical parameters to validate established and unravel novel biomarkers. We propose a hybrid approach where dimensionality reduction to a single axis is combined with multiple linked views allowing clinical experts to formulate hypotheses based on all available imaging data and clinical parameters. This may help to reveal novel tumor characteristics in relation to molecular targets for treatment, thus providing better tools for enabling more personalized targeted treatment strategies. To confirm the utility of our approach, we closely collaborate with experts from the field of gynecological cancer imaging and conducted an evaluation with six experts in this field.},
    pdf = "pdfs/Moerth-2020-RadEx.pdf",
    images = "images/Moerth-2020-RadEx.jpg",
    youtube = "",
    thumbnails = "images/Moerth-2020-RadEx-thumb.jpg",
    project = "ttmedvis",
    doi = {10.1111/cgf.14172}
    [PDF] [DOI] [YT] [Bibtex]
    author = "M\"{o}rth, E. and Haldorsen, I.S. and Bruckner, S. and Smit, N.N.",
    title = "ParaGlyder: Probe-driven Interactive Visual Analysis for Multiparametric Medical Imaging Data",
    booktitle = "Proceedings of Computer Graphics International",
    pages = "351--363",
    year = "2020",
    abstract = "Multiparametric medical imaging describes approaches that include multiple imaging sequences acquired within the same imaging examination, as opposed to one single imaging sequence or imaging from multiple imaging modalities. Multiparametric imaging in cancer has been shown to be useful for tumor detection and may also depict functional tumor characteristics relevant for clinical phenotypes. However, when confronted with datasets consisting of multiple values per voxel, traditional reading of the imaging series fails to capture complicated patterns. Those patterns of potentially important imaging properties of the parameter space may be critical for the analysis. Standard approaches, such as transfer functions and juxtapositioned visualizations, fail to convey the shape of the multiparametric parameter distribution in sufficient detail. For these reasons, in this paper we present an approach that aims to enable the exploration and analysis of such multiparametric studies using an interactive visual analysis application to remedy the trade-offs between details in the value domain and in spatial resolution. Interactive probing within or across subjects allows for a digital biopsy that is able to uncover multiparametric tissue properties. This may aid in the discrimination between healthy and cancerous tissue, unravel radiomic tissue features that could be linked to targetable pathogenic mechanisms, and potentially highlight metastases that evolved from the primary tumor. We conducted an evaluation with eleven domain experts from the field of gynecological cancer imaging, neurological imaging, and machine learning research to confirm the utility of our approach.",
    note= "The final authenticated version is available online at",
    pdf = "pdfs/Moerth-2020-CGI-ParaGlyder.pdf",
    images = "images/Moerth-2020-ParaGlyder.PNG",
    thumbnails = "images/Moerth-2020-ParaGlyder-thumb.png",
    youtube = "",
    publisher = "LNCS by Springer",
    project = "ttmedvis",
    doi = "10.1007/978-3-030-61864-3_29"


    [PDF] [DOI] [Bibtex]
    @inproceedings {Moerth-2019-VCBM,
    booktitle = "Eurographics Workshop on Visual Computing for Biology and Medicine",
    editor = "Kozlíková, Barbora and Linsen, Lars and Vázquez, Pere-Pau and Lawonn, Kai and Raidou, Renata Georgia",
    abstract = "Three-dimensional (3D) ultrasound imaging and visualization
    is often used in medical diagnostics, especially in prenatal
    screening. Screening the development of the fetus is
    important to assess possible complications early on. State
    of the art approaches involve taking standardized
    measurements to compare them with standardized tables. The
    measurements are taken in a 2D slice view, where precise
    measurements can be difficult to acquire due to the fetal
    pose. Performing the analysis in a 3D view would enable the
    viewer to better discriminate between artefacts and
    representative information. Additionally making data
    comparable between different investigations and patients is
    a goal in medical imaging techniques and is often achieved
    by standardization. With this paper, we introduce a novel
    approach to provide a standardization method for 3D
    ultrasound fetus screenings. Our approach is called “The
    Vitruvian Baby” and incorporates a complete pipeline for
    standardized measuring in fetal 3D ultrasound. The input of
    the method is a 3D ultrasound screening of a fetus and the
    output is the fetus in a standardized T-pose. In this pose,
    taking measurements is easier and comparison of different
    fetuses is possible. In addition to the transformation of
    the 3D ultrasound data, we create an abstract representation
    of the fetus based on accurate measurements. We demonstrate
    the accuracy of our approach on simulated data where the
    ground truth is known.",
    title = "The Vitruvian Baby: Interactive Reformation of Fetal Ultrasound Data to a T-Position",
    author = "M\"{o}rth, Eric and Raidou, Renata Georgia and Viola, Ivan and Smit, Noeska",
    year = "2019",
    publisher = "The Eurographics Association",
    ISSN = "2070-5786",
    ISBN = "978-3-03868-081-9",
    DOI = "10.2312/vcbm.20191245",
    pdf = "pdfs/VCBM_TheVitruvianBaby_ShortPaper_201-205.pdf",
    images = "images/vcbmVitruvianBaby.jpg",
    thumbnails = "images/vcbmVitruvianBaby.jpg",
    url = "",
    project = {VIDI}
    [PDF] [DOI] [Bibtex]
    @MISC {Moerth-2019-EUROVIS,
    booktitle = "EuroVis 2019 - Posters",
    editor = "Madeiras Pereira, João and Raidou, Renata Georgia",
    title = "The Vitruvian Baby: Interactive Reformation of Fetal Ultrasound Data to a T-Position",
    author = "M\"{o}rth, Eric and Raidou, Renata Georgia and Smit, Noeska and Viola, Ivan",
    year = "2019",
    abstract = "Three dimensional (3D) ultrasound is commonly used in prenatal screening, because it provides insight into the shape as well
    as the organs of the fetus. Currently, gynecologists take standardized measurements of the fetus and check for abnormalities by
    analyzing the data in a 2D slice view. The fetal pose may complicate taking precise measurements in such a view. Analyzing the
    data in a 3D view would enable the viewer to better distinguish between artefacts and representative information. Standardization
    in medical imaging techniques aims to make the data comparable between different investigations and patients. It is
    already used in different medical applications for example in magnetic resonance imaging (MRI). With this work, we introduce
    a novel approach to provide a standardization method for 3D ultrasound screenings of fetuses. The approach consists of six
    steps and is called “The Vitruvian Baby”. The input is the data of the 3D ultrasound screening of a fetus and the output shows
    the fetus in a standardized T-pose in which measurements can be made. The precision of standardized measurements compared
    to the gold standard is for the finger to finger span 91,08% and for the head to toe measurement 94,05%.",
    publisher = "The Eurographics Association",
    howpublished = "Poster presented at the EuroVis conference 2019",
    ISBN = "978-3-03868-088-8",
    DOI = "10.2312/eurp.20191147",
    pdf = "pdfs/EUROVIS_TheVitruvianBaby_Poster.pdf",
    images = "images/EUROVISTheVitruvianBabyPoster.png",
    thumbnails = "images/EUROVISTheVitruvianBabyPoster.png",
    url = ""