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Automated multistructure atlas‐assisted detection of lymph nodes using pelvic MR lymphography in prostate cancer patients

机译:使用盆腔癌患者在前列腺癌中使用盆腔MR淋巴扰动的自动化多体积图象辅助检测淋巴结

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Purpose: To investigate whether atlasbased anatomical information can improve a fully automated lymph node detection system for pelvic MR lymphography (MRL) images of patients with prostate cancer. Methods: Their data set contained MRL images of 240 prostate cancer patients who had an MRL as part of their clinical workup between January 2008 and April 2010, with ferumoxtran10 as contrast agent. Each MRL consisted of at least a 3D T1weighted sequence, a 3D T2*weighted sequence, and a FLASH3D sequence. The reference standard was created by two expert readers, reading in consensus, who annotated and interactively segmented the lymph nodes in all MRL studies. A total of 5089 lymph nodes were annotated. A fully automated computeraided detection (CAD) system was developed to find lymph nodes in the MRL studies. The system incorporates voxel features based on image intensities, the Hessian matrix, and spatial position. After feature calculation, a GentleBoostclassifier in combination with local maxima detection was used to identify lymph node candidates. Multiatlas based anatomical information was added to the CAD system to assess whether this could improve performance. Using histogram analysis and freereceiver operating characteristic analysis, this was compared to a strategy where relative position features were used to encode anatomical information. Results: Adding atlasbased anatomical information to the CAD system reduced false positive detections both visually and quantitatively. Median likelihood values of false positives decreased significantly in all annotated anatomical structures. The sensitivity increased from 53% to 70% at 10 false positives per lymph node. Conclusions: Adding anatomical information through atlas registration significantly improves an automated lymph node detection system for MRL images.
机译:目的:研究是否可以改善患有前列腺癌患者的骨盆MR淋巴训中(MRL)图像的全自动淋巴结检测系统。方法:他们的数据集包含了240例前列腺癌患者的MRL图像,作为2008年1月至2010年1月至2010年1月至2010年4月至2010年4月之间的临床次数的一部分,因为Ferumoxtran10为造影剂。每个MRL由至少3D T1重量序列,3D T2 *加权序列和Flash3D序列组成。参考标准由两个专家读者创建,在共识中阅读,他们在所有MRL研究中注释和交互地分割淋巴结。共注释共有5089次淋巴结。开发了一个全自动的计算机编写检测(CAD)系统以在MRL研究中找到淋巴结。该系统基于图像强度,黑森州矩阵和空间位置掺入体素特征。在特征计算之后,使用与局部最大值检测组合的柔滩灭菌剂用于鉴定淋巴结候选。基于Multiatlas的解剖信息被添加到CAD系统中以评估这是否可以提高性能。使用直方图分析和FreeReceiver操作特性分析,将其与使用相对位置特征用于编码解剖信息的策略进行比较。结果:将Atlasbased解剖信息添加到CAD系统视觉上和定量地减少了假阳性检测。所有注释的解剖结构中,假阳性的中位似然值显着下降。每个淋巴结的10个假阳性,敏感度从53%增加到70%。结论:通过阿特拉斯注册添加解剖学信息显着改善了MRL图像的自动淋巴结检测系统。

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