Automatic segmentation of non-enhancing brain tumors in magnetic resonance images
Automatic segmentation of non-enhancing brain tumors in magnetic resonance images
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DOI：
10.1016/s0933-3657(00)00073-7
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发表时间：
2001-01-01
影响因子：
7.5
通讯作者：
Murtagh, FR
中科院分区：
文献类型：
--
作者：
Fletcher-Heath, LM;Hall, LO;Murtagh, FR
来自磁共振（MR）图像的肿瘤分割可以通过跟踪肿瘤生长和/或收缩的进展来帮助肿瘤治疗。在本文中，我们提出了第一个自动分割方法，分离非增强脑肿瘤的健康组织的MR图像，以帮助跟踪肿瘤大小随时间的任务。用于分割的MR特征图像由通过头部的每个轴向切片的三个加权图像（T1、T2和质子密度（PD））组成。使用无监督模糊聚类算法计算初始分割。然后，综合领域知识和图像处理技术有助于最终的肿瘤分割。它们是在一个以知识为基础的系统的控制下应用的。通过在两个患者体积（14个图像）上训练来获取系统知识。测试表明，在四个患者体积（31张图像）上成功进行了肿瘤分割。我们的结果表明，我们检测到了所有六个非增强脑肿瘤，在36个包含肿瘤的地面实况（放射科医生标记的）切片中的35个中定位了肿瘤组织，并且在所有九个切片中成功地将肿瘤区域与物理连接的CSF区域分离。定量测量是有希望的，因为地面实况和分割的肿瘤区域之间的对应比率在每体积0.368和0.871之间，匹配百分比在每体积0.530和0.909之间。(C)2001 Elsevier Science B，V.保留所有权利。
Tumor segmentation from magnetic resonance (MR) images may aid in tumor treatment by tracking the progress of tumor growth and/or shrinkage. In this paper we present the first automatic segmentation method which separates non-enhancing brain tumors from healthy tissues in MR images to aid in the task of tracking tumor size over time. The MR feature images used for the segmentation consist of three weighted images (T1, T2 and proton density (PD)) for each axial slice through the head. An initial segmentation is computed using an unsupervised fuzzy clustering algorithm. Then, integrated domain knowledge and image processing techniques contribute to the final tumor segmentation. They are applied under the control of a knowledge-based system. The system knowledge was acquired by training on two patient volumes (14 images). Testing has shown successful tumor segmentations on four patient volumes (31 images). Our results show that we detected all six non-enhancing brain tumors, located tumor tissue in 35 of the 36 ground truth (radiologist labeled) slices containing tumor and successfully separated tumor regions from physically connected CSF regions in all the nine slices. Quantitative measurements are promising as correspondence ratios between ground truth and segmented tumor regions ranged between 0.368 and 0.871 per volume, with percent match ranging between 0.530 and 0.909 per volume. (C) 2001 Elsevier Science B,V. All rights reserved.