@article{Lima2024,
abstract = {This paper presents a brain tumor segmentation system for MRI images using Convolutional Neural Networks (CNNs). The goal is to assist in automated medical analysis by providing accurate segmentations of tumor areas to support diagnosis and treatment planning. The CNN model was trained on MRI images and accurately detected tumor boundaries. The proposed approach utilizes transfer learning to optimize the model's performance on high-resolution images, reducing processing time. The system stands out for its efficiency in segmenting tumors of various sizes and shapes, offering a promising tool for clinical neuroscience.},
author = {de Lima, Kau{\~{a}} Gabriel Silva and da Silva, Vagner Alves Ferreira and da Silva, Jo{\~{a}}o Victor Oliveira and de Oliveira, Lucas Patrick Ramos and da Silva, Diogo Lopes},
doi = {https://doi.org/10.51359/2965-4661.2024.265072},
journal = {Socioeconomic Analytics},
keywords = {Machine Learning,Neural Networks,healthcare,tumors},
number = {1},
pages = {114--120},
title = {{Using Convolutional Neural Networks for segmentation of brain tumors}},
url = {https://doi.org/10.51359/2965-4661.2024.265072},
volume = {2},
year = {2024}
}