Název: | Floor Map Visualizations of Medical Volume Data |
Autoři: | Merten, Nico Saalfeld, Sylvia Preim, Bernhard |
Citace zdrojového dokumentu: | Journal of WSCG. 2018, vol. 26, no. 1, p. 49-58. |
Datum vydání: | 2019 |
Nakladatel: | Václav Skala - UNION Agency |
Typ dokumentu: | článek article |
URI: | http://hdl.handle.net/11025/35586 |
ISSN: | 1213-6964 (on-line) 1213-6972 (print) 1213-6980 (CD-ROM) |
Klíčová slova: | půdorysy;podpora průzkumu zdravotnických objemových dat;abstrakce |
Klíčová slova v dalším jazyce: | floor maps;exploration support for medical volume data;abstraction |
Abstrakt v dalším jazyce: | Typically, volumetric medical image data is examined by assessing each slice of an image stack individually. However, this enables observers to assess in-plane spatial relationships between anatomical structures only and requires them to keep track of relationships along the third anatomical plane mentally. Therefore, visualization techniques are researched to support this task by depicting spatial information along the third plane, but they can introduce a high degree of abstraction. To overcome this, we present a novel approach that transforms image stacks with labeled anatomical structures into maps with a three-dimensional layout, namely floor maps. Since this approach increases the visual complexity under certain conditions, some clinical application scenarios, e. g. diagnosis and therapy planning, probably will not benefit. Thus, the approach is mainly aimed to support student training and the generation of clinical reports. We also discuss how to enhance the slice-based exploration of medical image stacks via floor maps and present the results of an informal evaluation with three trained anatomists. |
Práva: | © Václav Skala - UNION Agency |
Vyskytuje se v kolekcích: | Volume 27, Number 1 (2019) |
Soubory připojené k záznamu:
Soubor | Popis | Velikost | Formát | |
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Merten.pdf | Plný text | 3,95 MB | Adobe PDF | Zobrazit/otevřít |
Použijte tento identifikátor k citaci nebo jako odkaz na tento záznam:
http://hdl.handle.net/11025/35586
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