Automated Measurement of Ovary Development in Atlantic Salmon Using Deep Learning.

Journal: Ultrasound in medicine & biology
PMID: 38195265

Abstract

OBJECTIVE: Salmon breeding companies control the egg stripping period through environmental change, which triggers the need to identify the state of maturation. Ultrasound imaging of the salmon ovary is a proven non-invasive tool for this purpose; however, the process is laborious, and the interpretation of the ultrasound scans is subjective. Real-time ultrasound image segmentation of Atlantic salmon ovary provides an opportunity to overcome these limitations. However, several application challenges need to be addressed to achieve this goal. These challenges include the potential for false-positive and false-negative predictions, accurate prediction of attenuated lower ovary parts and resolution of inconsistencies in predicted ovary shape.

Authors

  • Yasin Yari
    Department of Circulation and Medical Imaging, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway. Electronic address: yasin.yari@ntnu.no.
  • Ingun Næve
    BDO AS, Trondheim, Norway; AquaGen AS, Trondheim, Norway.
  • Asle Hammerdal
    AquaGen AS, Trondheim, Norway.
  • Per Helge Bergtun
    MOWI AS, Trondheim, Norway.
  • Svein-Erik Måsøy
    Department of Circulation and Medical Imaging, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway.
  • Marco Marien Voormolen
    InPhase Solutions AS, Trondheim, Norway.
  • Lasse Lovstakken
    Department of Circulation and Medical Imaging, Norwegian University of Science and Technology, PO Box 8905, 7491 Trondheim, Norway.

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