监测缓慢进展的肿瘤。
MONITORING SLOWLY EVOLVING TUMORS.
作者信息
Konukoglu E, Wells W M, Novellas S, Ayache N, Kikinis R, Black P M, Pohl K M
机构信息
Asclepios Research Project, INRIA, Sophia Antipolis, France.
Brigham & Women's Hospital, Boston, MA.
出版信息
Proc IEEE Int Symp Biomed Imaging. 2008 May;2008:812-815. doi: 10.1109/ISBI.2008.4541120. Epub 2008 Jun 13.
Change detection is a critical task in the diagnosis of many slowly evolving pathologies. This paper describes an approach that semi-automatically performs this task using longitudinal medical images. We are specifically interested in meningiomas, which experts often find difficult to monitor as the tumor evolution can be obscured by image artifacts. We test the method on synthetic data with known tumor growth as well as ten clinical data sets. We show that the results of our approach highly correlate with expert findings but seem to be less impacted by inter- and intra-rater variability.
变化检测是许多缓慢发展的病症诊断中的一项关键任务。本文描述了一种使用纵向医学图像半自动执行此任务的方法。我们特别关注脑膜瘤，由于图像伪影可能会掩盖肿瘤的演变，专家们常常发现难以对其进行监测。我们在具有已知肿瘤生长情况的合成数据以及十个临床数据集上测试了该方法。我们表明，我们方法的结果与专家的发现高度相关，但似乎受评分者间和评分者内变异性的影响较小。
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