VCBM 19: Eurographics Workshop on Visual Computing for Biology and Medicine

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https://diglib.eg.org/handle/10.2312/2632802

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Browsing VCBM 19: Eurographics Workshop on Visual Computing for Biology and Medicine by Subject "Applications"

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    Colonic Content Assessment from MRI Imaging Using a Semi-automatic Approach
    (The Eurographics Association, 2019) Ceballos, Victor; Monclús, Eva; Vázquez, Pere-Pau; Bendezú, Álvaro; Mego, Marianela; Merino, Xavier; Azpiroz, Fernando; Navazo, Isabel; Kozlíková, Barbora and Linsen, Lars and Vázquez, Pere-Pau and Lawonn, Kai and Raidou, Renata Georgia
    The analysis of the morphology and content of the gut is necessary in order to achieve a better understanding of its metabolic and functional activity. Magnetic resonance imaging (MRI) has become an important imaging technique since it is able to visualize soft tissues in an undisturbed bowel using no ionizing radiation. In the last few years, MRI of gastrointestinal function has advanced substantially. However, few studies have focused on the colon, because the analysis of colonic content is time consuming and cumbersome. This paper presents a semi-automatic segmentation tool for the quantitative assessment of the unprepared colon from MRI images. The techniques developed here have been crucial for a number of clinical experiments.
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    A Visual Analytics Approach for Patient Stratification and Biomarker Discovery
    (The Eurographics Association, 2019) Alemzadeh, Shiva; Kromp, Florian; Preim, Bernhard; Taschner-Mandl, Sabine; Bühler, Katja; Kozlíková, Barbora and Linsen, Lars and Vázquez, Pere-Pau and Lawonn, Kai and Raidou, Renata Georgia
    We introduce discoVA as a visual analytics tool for the refinement of risk stratification of cancer patients and biomarker discovery. Currently, tools for the joint analysis of multiple biological and clinical information in this field are insufficient or lacking. Our tool fills this gap by enabling bio-medical experts to explore datasets of cancer patient cohorts. By using multiple coordinated visualization techniques, nested visual queries on various data types can be performed to generate/prove a hypothesis by identifying discrete sub-cohorts. We demonstrated the utility of discoVA by a case study involving bio-medical researchers.
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    Visual Analytics in Digital Pathology: Challenges and Opportunities
    (The Eurographics Association, 2019) Corvò, Alberto; Westenberg, Michel A.; Wimberger-Friedl, Reinhold; Fromme, Stephan; Peeters, Michel M. R.; Driel, Marc A. van; Wijk, Jarke J. van; Kozlíková, Barbora and Linsen, Lars and Vázquez, Pere-Pau and Lawonn, Kai and Raidou, Renata Georgia
    The advances in high-throughput digitization, digital pathology systems, and quantitative image analysis opened new horizons in pathology. The diagnostic work of the pathologists and their role is likely to be augmented with computer-assistance and more quantitative information at hand. The recent success of artificial intelligence (AI) and computer vision methods demonstrated that in the coming years machines will support pathologists in typically tedious and highly subjective tasks and also in better patient stratification. In spite of clear future improvements in the diagnostic workflow, questions on how to effectively support the pathologists and how to integrate current data sources and quantitative information still persist. In this context, Visual Analytics (VA) - as the discipline that aids users to solve complex problems with an interactive and visual approach - can play a vital role to support the cognitive skills of pathologists and the large volumes of data available. To identify the main opportunities to employ VA in digital pathology systems, we conducted a survey with 20 pathologists to characterize the diagnostic practice and needs from a user perspective. From our findings, we discuss how VA can leverage quantitative image data to empower pathologists with new advanced digital pathology systems.
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    A Web-based Application for the Visual Exploration of Colon Morphology Data
    (The Eurographics Association, 2019) Males, Jan; Monclús, Eva; Díaz, Jose; Vázquez, Pere-Pau; Kozlíková, Barbora and Linsen, Lars and Vázquez, Pere-Pau and Lawonn, Kai and Raidou, Renata Georgia
    The colon is an organ whose constant motility poses difficulties to its analysis. Although morphological data can be successfully extracted from Computational Tomography, its radiative nature makes it only indicated for patients with disorders. Only recently, acquisition techniques that rely on the use of Magnetic Resonance Imaging have matured enough to enable the generation of morphological colon data of healthy patients without preparation (i. e. administration of drugs or contrast agents). As a result, a database of colon morphological data for patients under different diets, has been created. Currently, the digestologists we collaborate with analyze the measured data of the gut by inspecting a set of spreadsheets. In this paper, we propose a system for the exploratory visual analysis of the whole database of morphological data at once. It provides features for the visual comparison of data correlations, the inspection of the morphological measures, as well 3D rendering of the colon segmented models. The system solely relies on the use of web technologies, which makes it portable even to mobile devices.