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Combining registration and active shape models for the automatic segmentation of the lymph node regions in head and neck CT images

机译:结合套准模型和主动形状模型以自动分割头颈部CT图像中的淋巴结区域

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摘要

Purpose: Intensity-modulated radiation therapy (IMRT) is the state of the art technique for head and neck cancer treatment. It requires precise delineation of the target to be treated and structures to be spared, which is currently done manually. The process is a time-consuming task of which the delineation of lymph node regions is often the longest step. Atlas-based delineation has been proposed as an alternative, but, in the authors’ experience, this approach is not accurate enough for routine clinical use. Here, the authors improve atlas-based segmentation results obtained for level II–IV lymph node regions using an active shape model (ASM) approach.
机译:目的:调强放射疗法(IMRT)是用于治疗头颈癌的最新技术。它需要精确地描述要治疗的目标和要保留的结构,这目前是手动完成的。该过程是一项耗时的任务,其中划定淋巴结区域通常是最长的步骤。已经提出了基于Atlas的轮廓作为替代方案,但是根据作者的经验,这种方法对于常规临床使用而言不够准确。在这里,作者使用主动形状模型(ASM)方法改善了针对II–IV级淋巴结区域获得的基于图集的分割结果。

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