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MSCF: Multi-Scale Canny Filter to Recognize Cells in Microscopic Images

Author

Listed:
  • Almoutaz Mbaidin

    (Computer Science Department, Mutah University, Karak 61711, Jordan
    Centro Singular de Investigación en Tecnoloxías Intelixentes da USC (CiTIUS), Universidade de Santiago de Compostela, 15705 Santiago de Compostela, Spain)

  • Eva Cernadas

    (Centro Singular de Investigación en Tecnoloxías Intelixentes da USC (CiTIUS), Universidade de Santiago de Compostela, 15705 Santiago de Compostela, Spain)

  • Zakaria A. Al-Tarawneh

    (Computer Science Department, Mutah University, Karak 61711, Jordan)

  • Manuel Fernández-Delgado

    (Centro Singular de Investigación en Tecnoloxías Intelixentes da USC (CiTIUS), Universidade de Santiago de Compostela, 15705 Santiago de Compostela, Spain)

  • Rosario Domínguez-Petit

    (Instituto Español de Oceanografía (IEO, CSIC), Centro Oceanográfico de Vigo, 36390 Vigo, Spain)

  • Sonia Rábade-Uberos

    (Instituto de Investigaciones Marinas (IIM, CSIC), Calle Eduardo Cabello 6, 36208 Vigo, Spain)

  • Ahmad Hassanat

    (Computer Science Department, Mutah University, Karak 61711, Jordan)

Abstract

Fish fecundity is one of the most relevant parameters for the estimation of the reproductive potential of fish stocks, used to assess the stock status to guarantee sustainable fisheries management. Fecundity is the number of matured eggs that each female fish can spawn each year. The stereological method is the most accurate technique to estimate fecundity using histological images of fish ovaries, in which matured oocytes must be measured and counted. A new segmentation technique, named the multi-scale Canny filter (MSCF), is proposed to recognize the boundaries of cells (oocytes), based on the Canny edge detector. Our results show the superior performance of MSCF on five fish species compared to five other state-of-the-art segmentation methods. It provides the highest F 1 score in four out of five fish species, with values between 70% and 80%, and the highest percentage of correctly recognized cells, between 52% and 64%. This type of research aids in the promotion of sustainable fisheries management and conservation efforts, decreases research’s environmental impact and gives important insights into the health of fish populations and marine ecosystems.

Suggested Citation

  • Almoutaz Mbaidin & Eva Cernadas & Zakaria A. Al-Tarawneh & Manuel Fernández-Delgado & Rosario Domínguez-Petit & Sonia Rábade-Uberos & Ahmad Hassanat, 2023. "MSCF: Multi-Scale Canny Filter to Recognize Cells in Microscopic Images," Sustainability, MDPI, vol. 15(18), pages 1-16, September.
  • Handle: RePEc:gam:jsusta:v:15:y:2023:i:18:p:13693-:d:1239263
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