Evaluation of the Detection Capabilities of Ovarian Structures in Ultrasound Images of Cows Using Convolutional Neural Networks

• João Moura Unifesspa
• Marcela Alves Unifesspa
• Hugo Kuribayashi Unifesspa
• André Cascalho Unifesspa
• Adam Santos Unifesspa

DOI: https://doi.org/10.5753/eniac.2025.11790

Resumo

Ultrasound plays a crucial role in veterinary medicine, being widely used for the detection of diseases and the identification of reproductive conditions in animals in a less invasive and more cost-effective manner. However, the effectiveness of this method is highly dependent on the experience and training of the professional conducting the analysis, as the relatively low quality of the generated images can hinder accurate interpretation of the results. This study evaluates the ability to detect ovarian structures in a cow ultrasound image dataset using convolutional neural networks with the YoloV8 model. The results demonstrated high accuracy in the task, achieving approximately 90% accuracy in detecting objects of interest.

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