基于卷积神经网络的医学图像自动分割

Sourour Mesbahi, Hedi Yazid
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引用次数: 2

摘要

提出了一种用于医学图像分割的神经网络结构。我们选择测试和实现各种卷积神经网络(CNN)。我们选择将这项工作应用于包含脑肿瘤的脑图像分割主题。主要目的是在处理一个小数据库的同时,选择应用于MRI脑肿瘤任务的最佳架构和参数化。使用我们的个性化CNN架构进行的分割和学习评估测试显示了良好的性能。
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Automatic segmentation of medical images using convolutional neural networks
This paper presents a neural network architecture for segmentation of medical images. We have chosen to test and implement various Convolutional Neural Network (CNN). We chose to apply this work on a topic of cerebral images segmentation containing brain tumors. The main objective is to choose the best architecture and parameterization applied into a task of a MRI brain tumor while treating a small database. Segmentation and learning assessment tests show good performance using our personalized CNN architecture.
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