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Plexiform Neurofibroma tissue classification

机译:丛形神经纤维瘤组织分类

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Plexiform Neurofibroma (PN) is a major complication of NeuroFibromatosis-1 (NFl), a common genetic disease that involving the nervous system. PNs are peripheral nerve sheath tumors extending along the length of the nerve in various parts of the body. Treatment decision is based on tumor volume assessment using MRI, which is currently time consuming and error prone, with limited semi-automatic segmentation support. We present in this paper a new method for the segmentation and tumor mass quantification of PN from STIR MRI scans. The method starts with a user-based delineation of the tumor area in a single slice and automatically detects the PN lesions in the entire image based on the tumor connectivity. Experimental results on seven datasets yield a mean volume overlap difference of 25% as compared to manual segmentation by expert radiologist with a mean computation and interaction time of 12 minutes vs. over an hour for manual annotation. Since the user interaction in the segmentation process is minimal, our method has the potential to successfully become part of the clinical workflow.
机译:丛状神经纤维瘤(PN)是神经纤维瘤病-1(NFL)的主要并发症,涉及神经系统的常见遗传疾病。 PNS是沿着身体各个部位的神经长度延伸的外周神经鞘肿瘤。治疗决策是基于使用MRI的肿瘤体积评估,目前是耗时和易于出错的,具有有限的半自动分割支持。本文介绍了搅拌MRI扫描中PN分割和肿瘤质量的新方法。该方法从单个切片中的基于用户的描绘开始,并且基于肿瘤连接自动检测整个图像中的PN病变。七个数据集的实验结果产生平均体积重叠差异为25%,而专家放射科医生的手动分割相比,平均计算和12分钟的相互作用时间与一个小时进行手动注释。由于分段过程中的用户交互是最小的,因此我们的方法有可能成功成为临床工作流程的一部分。

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