3D brain tumor segmentation in MRI using fuzzy classification, symmetry analysis and spatially constrained deformable models
3D brain tumor segmentation in MRI using fuzzy classification, symmetry analysis and spatially constrained deformable models
复制标题
DOI：
10.1016/j.fss.2008.11.016
复制
发表时间：
2009-05-16
影响因子：
3.9
通讯作者：
Bloch, Isabelle
中科院分区：
文献类型：
--
作者：
Khotanlou, Hassan;Colliot, Olivier;Bloch, Isabelle
提出了一种新的三维磁共振图像中脑肿瘤分割的通用方法。我们的方法适用于不同类型的肿瘤。首先，使用一种新的方法对大脑进行分割，对肿瘤的存在具有很强的抵抗力。然后，基于选择相对于近似脑对称平面的不对称区域和模糊分类来执行第一肿瘤检测。它的结果构成了基于可变形模型和空间关系的组合的分割方法的初始化，导致了对肿瘤的精确分割。使用适当的模糊模型，在所有级别都考虑到了不精确度和可变性。通过与人工分割的比较，对不同类型肿瘤的分割结果进行了评估。(C)2008爱思唯尔B.V.保留所有权利。
We propose a new general method for segmenting brain tumors in 3D magnetic resonance images. Our method is applicable to different types of tumors. First, the brain is segmented using a new approach, robust to the presence of tumors. Then a first tumor detection is performed, based on selecting asymmetric areas with respect to the approximate brain symmetry plane and fuzzy classification. Its result constitutes the initialization of a segmentation method based on a combination of a deformable model and spatial relations, leading to a precise segmentation of the tumors. Imprecision and variability are taken into account at all levels, using appropriate fuzzy models. The results obtained on different types of tumors have been evaluated by comparison with manual segmentations. (C) 2008 Elsevier B.V. All rights reserved.