COMPARISON OF SUPERVISED MRI SEGMENTATION METHODS FOR TUMOR VOLUME DETERMINATION DURING THERAPY
COMPARISON OF SUPERVISED MRI SEGMENTATION METHODS FOR TUMOR VOLUME DETERMINATION DURING THERAPY
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DOI：
10.1016/0730-725x(95)00012-6
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发表时间：
1995-01-01
影响因子：
2.5
通讯作者：
SILBIGER, M
中科院分区：
文献类型：
--
作者：
VAIDYANATHAN, M;CLARKE, LP;SILBIGER, M
两种不同的多光谱模式识别方法被用于分割脑的磁共振图像(MRI)，以定量估计肿瘤体积和治疗后的体积变化。使用监督k近邻(KNN)规则和半监督模糊C均值(SFCM)方法来分割MRI切片数据，将KNN和SFCM分割方法确定的肿瘤体积与两种基于图像灰度级的参考方法进行比较，作为基本事实估计的基础，即：(A)应用于对比度增强的T-1加权图像的常用种子生长方法，以及(B)使用应用于相同原始图像(T-1加权)数据集的定制设计的图形用户界面的手动分割方法，重点是使用所提出的方法来测量观察者内和观察者间的重复性。KNN方法的观察者内变异为9%，观察者间变异为5%，SFCM方法的结果稍好，分别为6%和4%；种子生长法的观察者内变异为6%，观察者间变异为17%，明显大于多光谱方法。多光谱分割方法确定的绝对肿瘤体积始终小于参考方法所观察到的体积。这项研究的结果被发现非常依赖于患者的病例。SFCM的结果表明，它对于治疗期间肿瘤体积的相对测量应该是有用的，但还需要进一步的研究，这项工作证明了对肿瘤体积测量的最小监督或非监督方法的必要性。
Two different multispectral pattern recognition methods are used to segment magnetic resonance images (MRI) of the brain for quantitative estimation of tumor volume and volume changes with therapy. A supervised k-nearest neighbor (kNN) rule and a semi-supervised fuzzy c-means (SFCM) method are used to segment MRI slice data, Tumor volumes as determined by the kNN and SFCM segmentation methods are compared with two reference methods, based on image grey scale, as a basis for an estimation of ground truth, namely: (a) a commonly used seed growing method that is applied to the contrast enhanced T-1-weighted image, and (b) a manual segmentation method using a custom-designed graphical user interface applied to the same raw image (T-1-weighted) dataset, Emphasis is placed on measurement of intra and inter observer reproducibility using the proposed methods. Intra-and interobserver variation for the kNN method was 9% and 5%, respectively, The results for the SFCM method was a little better at 6% and 4%, respectively, For the seed growing method, the intra-observer variation was 6% and the interobserver variation was 17%, significantly larger when compared with the multispectral methods. The absolute tumor volume determined by the multispectral segmentation methods was consistently smaller than that observed for the reference methods. The results of this study are found to be very patient case-dependent. The results for SFCM suggest that it should be useful for relative measurements of tumor volume during therapy, but further studies are required, This work demonstrates the need for minimally supervised or unsupervised methods for tumor volume measurements.