The use of atlas registration and graph cuts for prostate segmentation in magnetic resonance images
The use of atlas registration and graph cuts for prostate segmentation in magnetic resonance images
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DOI：
10.1118/1.4914379
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发表时间：
2015-04-01
期刊：
影响因子：
3.8
通讯作者：
van Walsum, Theo
中科院分区：
文献类型：
--
作者：
Korsager, Anne Sofie;Fortunati, Valerio;van Walsum, Theo
目的：提出了一种在磁共振（MR）图像中进行前列腺三维自动分割的方法，用于规划图像引导的前列腺癌放射治疗。方法：将基于受试者间图谱配准的空间先验与器官特异性强度信息相结合，在图切割分割框架中。在留一法交叉验证实验中，对67个轴向T-2加权MR图像进行了分割测试，并与手动参考分割和使用多数投票图谱融合的基于多图谱的分割进行了比较。在传统的基于图谱的分割和新的图切割方法，结合图谱和强度信息，以提高分割精度的图谱选择的影响进行了研究。结果：与手工描绘相比，Dice相似性系数（DSC）平均为0.88，表面距离（MSD）平均为1.45 mm。结论：这接近0.90的观察者间DSC和1.15 mm的观察者间MSD，并且与MR（C）2015美国医学物理学家协会中进行前列腺分割的其他研究相当。
Purpose: An automatic method for 3D prostate segmentation in magnetic resonance (MR) images is presented for planning image-guided radiotherapy treatment of prostate cancer.Methods: A spatial prior based on intersubject atlas registration is combined with organ-specific intensity information in a graph cut segmentation framework. The segmentation is tested on 67 axial T-2-weighted MR images in a leave-one-out cross validation experiment and compared with both manual reference segmentations and with multiatlas-based segmentations using majority voting atlas fusion. The impact of atlas selection is investigated in both the traditional atlas-based segmentation and the new graph cut method that combines atlas and intensity information in order to improve the segmentation accuracy. Best results were achieved using the method that combines intensity information, shape information, and atlas selection in the graph cut framework.Results: A mean Dice similarity coefficient (DSC) of 0.88 and a mean surface distance (MSD) of 1.45 mm with respect to the manual delineation were achieved.Conclusions: This approaches the interobserver DSC of 0.90 and interobserver MSD 0f 1.15 mm and is comparable to other studies performing prostate segmentation in MR. (C) 2015 American Association of Physicists in Medicine.