Cristin-resultat-ID: 2018858
Sist endret: 17. februar 2023, 12:01
NVI-rapporteringsår: 2022
Resultat
Vitenskapelig artikkel
2022

FishSizer: Software solution for efficiently measuring larval fish size

Bidragsytere:
  • Jeppe Have Rasmussen
  • Marta Moyano
  • Lee A. Fuiman og
  • Rebekah Alice Oomen

Tidsskrift

Ecology and Evolution
ISSN 2045-7758
e-ISSN 2045-7758
NVI-nivå 1

Om resultatet

Vitenskapelig artikkel
Publiseringsår: 2022
Volum: 12
Hefte: 3
Sider: 1 - 10
Artikkelnummer: e8672
Open Access

Importkilder

Scopus-ID: 2-s2.0-85127333850

Beskrivelse Beskrivelse

Tittel

FishSizer: Software solution for efficiently measuring larval fish size

Sammendrag

Length and depth of fish larvae are part of the fundamental measurements in many marine ecology studies involving early fish life history. Until now, obtaining these measurements has required intensive manual labor and the risk of inter- and intra-observer variability. We developed an open-source software solution to semi-automate the measurement process and thereby reduce both time consumption and technical variability. Using contrast-based edge detection, the software segments images of a fish larva into “larva” and “background.” Length and depth are extracted from the “larva” segmentation while taking curvature of the larva into consideration. The graphical user interface optimizes workflow and ease of usage, thereby reducing time consumption for both training and analysis. The software allows for visual verification of all measurements. A comparison of measurement methods on a set of larva images showed that this software reduces measurement time by 66%–78% relative to commonly used software. Using this software instead of the commonly used manual approach has the potential to save researchers from many hours of monotonous work. No adjustment was necessary for 89% of the images regarding length (70% for depth). Hence, the only workload on most images was the visual inspection. As the visual inspection and manual dimension extraction works in the same way as currently used software, we expect no loss in accuracy.

Bidragsytere

Jeppe Have Rasmussen

  • Tilknyttet:
    Forfatter
    ved Institutt for naturvitenskapelige fag ved Universitetet i Agder

Marta Moyano

  • Tilknyttet:
    Forfatter
    ved Institutt for naturvitenskapelige fag ved Universitetet i Agder

Lee A. Fuiman

  • Tilknyttet:
    Forfatter
    ved University of Texas at Austin

Rebekah Alice Oomen

  • Tilknyttet:
    Forfatter
    ved Institutt for naturvitenskapelige fag ved Universitetet i Agder
  • Tilknyttet:
    Forfatter
    ved Centre for Ecological and Evolutionary Synthesis ved Universitetet i Oslo
1 - 4 av 4