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Article

STERapp: Semiautomatic Software for Stereological Analysis. Application in the Estimation of Fish Fecundity

1
Centro Singular de Investigación en Tecnoloxías Intelixentes da USC (CiTIUS), Universidade de Santiago de Compostela, Rúa Xenaro de la Fuente Domínguez, 15782 Santiago de Compostela, Spain
2
Instituto de Investigaciones Marinas, CSIC, Calle Eduardo Cabello 6, 36208 Vigo, Spain
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Centro Oceanográfico de Vigo, Instituto Español de Oceanografía (IEO, CSIC), Subida a Radiofaro, 50-52, 36390 Vigo, Spain
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Laboratorio de Informática Aplicada (LIA2), Departamento de Informática, Campus Universitario, Universidade de Vigo, Edifício Politécnico s/n, 32004 Ourense, Spain
*
Author to whom correspondence should be addressed.
Academic Editor: Jordi Guitart
Electronics 2021, 10(12), 1432; https://doi.org/10.3390/electronics10121432
Received: 16 April 2021 / Revised: 31 May 2021 / Accepted: 5 June 2021 / Published: 15 June 2021
(This article belongs to the Special Issue Applications of Computer Vision)
Stereology is the tridimensional interpretation of bidimensional sections of a structure, widely used in fields such as mineralogy, medicine, and biology. This paper proposes a general software to do stereological analysis, called STERapp, with a friendly graphical interface to enable expert supervision. It includes a module to estimate fish fecundity (number of mature oocytes in the ovary), which has been used by experts in fish biology in two Spanish marine research centers since 2020 to estimate the fecundity of five fish species with different reproductive strategies and oocytes characteristics. This module encloses advanced computer vision and machine learning techniques to automatically recognize and classify the cells in histological images of fish gonads. The automatic recognition algorithm achieved a sensitivity of 55.6%, a specificity of 64.8%, and an average precision of 43.1%. The accuracies achieved for oocyte classification were 84.5% for the maturity stages and 78.5% for the classification regarding presence/absence of the nucleus. This facilitates the analysis and saves experts’ time. Hence, the SUS questionnaire reported a mean score of 81.9, which means that the system was perceived from good to excellent to develop stereological analysis for the estimation of fish fecundity. View Full-Text
Keywords: stereology; texture analysis; classification; support vector machine; software engineering; image segmentation; fecundity methods; oocytes; recognition; Weibel grid stereology; texture analysis; classification; support vector machine; software engineering; image segmentation; fecundity methods; oocytes; recognition; Weibel grid
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MDPI and ACS Style

Mbaidin, A.; Rábade-Uberos, S.; Dominguez-Petit, R.; Villaverde, A.; Gónzalez-Rufino, M.E.; Formella, A.; Fernández-Delgado, M.; Cernadas, E. STERapp: Semiautomatic Software for Stereological Analysis. Application in the Estimation of Fish Fecundity. Electronics 2021, 10, 1432. https://doi.org/10.3390/electronics10121432

AMA Style

Mbaidin A, Rábade-Uberos S, Dominguez-Petit R, Villaverde A, Gónzalez-Rufino ME, Formella A, Fernández-Delgado M, Cernadas E. STERapp: Semiautomatic Software for Stereological Analysis. Application in the Estimation of Fish Fecundity. Electronics. 2021; 10(12):1432. https://doi.org/10.3390/electronics10121432

Chicago/Turabian Style

Mbaidin, Almoutaz, Sonia Rábade-Uberos, Rosario Dominguez-Petit, Andrés Villaverde, María E. Gónzalez-Rufino, Arno Formella, Manuel Fernández-Delgado, and Eva Cernadas. 2021. "STERapp: Semiautomatic Software for Stereological Analysis. Application in the Estimation of Fish Fecundity" Electronics 10, no. 12: 1432. https://doi.org/10.3390/electronics10121432

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