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Segmentation of brain MRI using active contour model

机译:使用主动轮廓模型对脑MRI进行分割

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Alzheimer disease is a neurodegenerative disorder that impairs memory, cognitive function, and gradually leads to dementia, physical deterioration, loss of independence, and death of the affected individual. In this context, segmentation of medical images is a very important technique in the field of image analysis and Computer-Assisted Diagnosis. In this article, we introduce a new automatic method of brain images' segmentation based on the Active Contour (AC) model to extract the Hippocampus and the Corpus Callosum (CC). Our contribution is to combine the geometric method with the statistical method of the AC. We used the Caselle Level Set and added a learning phase to build an average shape and to make the initialization task automatic. For the step of contour evolution, we used the principle of Level set and we added to it the a priori knowledge. Experimental results are very promising. (C) 2017 Wiley Periodicals, Inc.
机译:阿尔茨海默氏病是一种神经退行性疾病,会损害记忆力,认知功能,并逐渐导致痴呆,身体退化,丧失独立性以及受影响的个体死亡。在这种情况下,医学图像的分割是图像分析和计算机辅助诊断领域中非常重要的技术。在本文中,我们介绍了一种基于主动轮廓(AC)模型的脑图像自动分割方法,该方法可提取海马和the体(CC)。我们的贡献是将几何方法与AC的统计方法相结合。我们使用了Caselle Level Set,并添加了一个学习阶段来构建平均形状并使初始化任务自动进行。对于轮廓演化的步骤,我们使用了“水平集”的原理,并向其添加了先验知识。实验结果很有希望。 (C)2017威利期刊公司

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