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TopoAngler: Interactive Topology-Based Extraction of Fishes
New York University, USA.ORCID iD: 0000-0002-2849-6146
New York University, USA.
New York University, USA.
University of Washington, USA.
2018 (English)In: IEEE Transactions on Visualization and Computer Graphics, ISSN 1077-2626, E-ISSN 1941-0506, Vol. 24, no 1, p. 812-821Article in journal (Refereed) Published
Abstract [en]

We present TopoAngler, a visualization framework that enables an interactive user-guided segmentation of fishes contained in a micro-CT scan. The inherent noise in the CT scan coupled with the often disconnected (and sometimes broken) skeletal structure of fishes makes an automatic segmentation of the volume impractical. To overcome this, our framework combines techniques from computational topology with an interactive visual interface, enabling the human-in-the-Ioop to effectively extract fishes from the volume. In the first step, the join tree of the input is used to create a hierarchical segmentation of the volume. Through the use of linked views, the visual interface then allows users to interactively explore this hierarchy, and gather parts of individual fishes into a coherent sub-volume, thus reconstructing entire fishes. Our framework was primarily developed for its application to CT scans of fishes, generated as part of the ScanAllFish project, through close collaboration with their lead scientist. However, we expect it to also be applicable in other biological applications where a single dataset contains multiple specimen; a common routine that is now widely followed in laboratories to increase throughput of expensive CT scanners.

Place, publisher, year, edition, pages
IEEE, 2018. Vol. 24, no 1, p. 812-821
Keywords [en]
branch decomposition, Computational topology, hierarchical segmentation, interaction, join trees, visualization system
National Category
Human Computer Interaction
Identifiers
URN: urn:nbn:se:liu:diva-158035DOI: 10.1109/TVCG.2017.2743980OAI: oai:DiVA.org:liu-158035DiVA, id: diva2:1329096
Available from: 2019-06-24 Created: 2019-06-24 Last updated: 2019-10-22

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