Using Convolutional Neural Networks for segmentation of brain tumors
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 image...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Universidade Federal de Pernambuco (UFPE)
2024-12-01
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| Series: | Socioeconomic Analytics |
| Subjects: | |
| Online Access: | https://periodicos.ufpe.br/revistas/index.php/SECAN/article/view/265072 |
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| Summary: | 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 demonstrated high accuracy in detecting 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
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| ISSN: | 2965-4661 |