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Definition and Automatic Anatomy Recognition of Lymph Node Zones in the Pelvis on CT Images

机译:CT图像上骨盆淋巴结区的定义和自动解剖识别

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Currently, unlike IALSC-defined thoracic lymph node zones, no explicitly provided definitions for lymph nodes in other body regions are available. Yet, definitions are critical for standardizing the recognition, delineation, quantification, and reporting of lymphadenopathy in other body regions. Continuing from our previous work in the thorax, this paper proposes a standardized definition of the grouping of pelvic lymph nodes into 10 zones. We subsequently employ our earlier Automatic Anatomy Recognition (AAR) framework designed for body-wide organ modeling, recognition, and delineation to actually implement these zonal definitions where the zones are treated as anatomic objects. First, all 10 zones and key anatomic organs used as anchors are manually delineated under expert supervision for constructing fuzzy anatomy models of the assembly of organs together with the zones. Then, optimal hierarchical arrangement of these objects is constructed for the purpose of achieving the best zonal recognition. For actual localization of the objects, two strategies are used - optimal thresholded search for organs and one-shot method for the zones where the known relationship of the zones to key organs is exploited. Based on 50 computed tomography (CT) image data sets for the pelvic body region and an equal division into training and test subsets, automatic zonal localization within 1-3 voxels is achieved.
机译:目前,与IALSC定义的胸淋巴结区不同,没有明确提供其他身体区域的淋巴结的定义。然而,定义对于标准化识别,描绘,定量和报告在其他身体区域中的淋巴结病变和报告至关重要。从我们以前的工作中继续在胸部中的工作中,本文提出了将盆腔淋巴结分组成10个区域的标准化定义。我们随后使用我们的早期自动解剖识别(AAR)框架,专为身体宽的器官建模,识别和描绘而实际实施这些区域定义,其中区被视为解剖物对象。首先,所有10区和用作锚的钥匙解剖器在专家监督下手动描绘,用于构建器官组装的模糊解剖模型以及区内的模糊解剖模型。然后,为实现最佳区内识别的目的,构造这些对象的最佳分层布置。对于对象的实际本地化,使用了两种策略 - 用于利用区域与关键器官的已知关系的区域的机器官和单次方法的最佳阈值。基于50个计算机断层扫描(CT)图像数据集,用于盆腔体区域和等级分为训练和测试子集,实现1-3体素内的自动区间定位。

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