DSpace Coleção:https://repositorio.uema.br/jspui/handle/123456789/22012026-07-10T07:28:20Z2026-07-10T07:28:20ZAutomatização do reconhecimento de células germinativas em imagens histológicas de ovários de peixes: estudo de caso de peixes encontrados no estado do Maranhãohttps://repositorio.uema.br/jspui/handle/123456789/62502026-07-02T19:50:46Z2025-02-17T00:00:00ZTítulo: Automatização do reconhecimento de células germinativas em imagens histológicas de ovários de peixes: estudo de caso de peixes encontrados no estado do Maranhão
Abstact: The state of Maranhão has significant fishing activity, making it essential to monitor the
reproductive biology of fish for sustainable management. This work presents an automated
approach for recognizing germ cells in histological images of fish ovaries, using digital image
processing and supervised learning. The objective is to develop a tool that aids in the efficient
analysis of gonads, contributing to knowledge in the field and better management of fishing
resources. The methodology uses the Canny edge detection algorithm to segment cells and
supervised learning techniques to classify them, overcoming the limitations of traditional
manual methods. The results show gains in batch processing speed (50 images/minute) and
precision (56% accuracy) with STERapp. The solution aims to increase the precision and
reproducibility of analyses, positively impacting fishing sustainability in Maranhão and similar
regions2025-02-17T00:00:00Z