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Unwind: Interactive Fish Straightening
NYU, NY 10003 USA.
Linköping University, Department of Science and Technology, Media and Information Technology. Linköping University, Faculty of Science & Engineering.ORCID iD: 0000-0002-2849-6146
NYU, NY 10003 USA.
Tufts Univ, MA 02155 USA.
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2020 (English)In: PROCEEDINGS OF THE 2020 CHI CONFERENCE ON HUMAN FACTORS IN COMPUTING SYSTEMS (CHI20), ASSOC COMPUTING MACHINERY , 2020Conference paper, Published paper (Refereed)
Abstract [en]

The ScanAllFish project is a large-scale effort to scan all the worlds 33,100 known species of fishes. It has already generated thousands of volumetric CT scans of fish species which are available on open access platforms such as the Open Science Framework. To achieve a scanning rate required for a project of this magnitude, many specimens are grouped together into a single tube and scanned all at once. The resulting data contain many fish which are often bent and twisted to fit into the scanner. Our system, Unwind, is a novel interactive visualization and processing tool which extracts, unbends, and untwists volumetric images of fish with minimal user interaction. Our approach enables scientists to interactively unwarp these volumes to remove the undesired torque and bending using a piecewise-linear skeleton extracted by averaging iso-surfaces of a harmonic function connecting the head and tail of each fish. The result is a volumetric dataset of a individual, straight fish in a canonical pose defined by the marine biologist expert user. We have developed Unwind in collaboration with a team of marine biologists: Our system has been deployed in their labs, and is presently being used for dataset construction, biomechanical analysis, and the generation of figures for scientific publication.

Place, publisher, year, edition, pages
ASSOC COMPUTING MACHINERY , 2020.
Keywords [en]
CT Scan Data; Volumetric Deformation; Interactive System
National Category
Fish and Aquacultural Science
Identifiers
URN: urn:nbn:se:liu:diva-180541DOI: 10.1145/3313831.3376846ISI: 000696110400135ISBN: 9781450367080 (print)OAI: oai:DiVA.org:liu-180541DiVA, id: diva2:1605977
Conference
CHI Conference on Human Factors in Computing Systems (CHI), ELECTR NETWORK, apr 25-30, 2020
Note

Funding Agencies|Moore-Sloan Data Science Environment at NYU; NASANational Aeronautics & Space Administration (NASA); NSFNational Science Foundation (NSF) [DBI-1759637, OAC-1835712, CHF-1908767, NSF IIS-1901091, CNS-1229185, CCF-1533564, CNS-1544753, CNS-1828576, CNS1626098, CNS-1730396]; NSF CAREER awardNational Science Foundation (NSF)NSF - Office of the Director (OD) [1652515]; Seaver Institute; DARPA D3M program; NVIDIA NVAIL at NYU

Available from: 2021-10-26 Created: 2021-10-26 Last updated: 2021-10-26

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Citation style
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