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首页> 外文期刊>Magnetic resonance in medicine: official journal of the Society of Magnetic Resonance in Medicine >Improving the segmentation of therapy-induced leukoencephalopathy in children with acute lymphoblastic leukemia using a priori information and a gradient magnitude threshold.
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Improving the segmentation of therapy-induced leukoencephalopathy in children with acute lymphoblastic leukemia using a priori information and a gradient magnitude threshold.

机译:使用先验信息和梯度幅度阈值改善急性淋巴细胞白血病儿童治疗性白细胞脑病的细分。

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Reliably quantifying therapy-induced leukoencephalopathy is a challenging task due to the similarity between its MR properties and those of normal tissues. Multispectral MR images were analyzed for 15 children treated for acute lymphoblastic leukemia. Three different analysis techniques were compared to examine improvements in the segmentation accuracy of leukoencephalopathy versus manual tracings by two experienced observers. The original technique used a white matter mask based on the segmentation of the first serial examination of each patient and no a priori information. The modified techniques combine spatially normalized a priori maps as input and a gradient magnitude threshold. The second technique used a 2D threshold, while the third algorithm utilized a 3D threshold. MR images were segmented with a Kohonen self-organizing map for all three algorithms. Kappa values were compared for the three techniques to each observer and statistically significant improvements were seen between the original and third algorithms (Observer 1: 0.651, 0.744, P = 0.015; Observer 2: 0.603, 0.699, P = 0.024). More accurate and reliable quantification reduces the amount of variance in MR measures and facilitates clinical trials to determine the clinical significance of leukoencephalopathy in this vulnerable population.
机译:由于其MR特性与正常组织的MR特性相似,因此可靠地量化治疗引起的白质脑病是一项艰巨的任务。分析了15例接受急性淋巴细胞白血病治疗的儿童的多光谱MR图像。比较了三种不同的分析技术,以检查两名经验丰富的观察者对白质脑病分割精度与手动描迹的提高。原始技术使用白质掩膜,其基于每个患者的第一次连续检查的分割,并且没有先验信息。修改后的技术将空间归一化的先验图作为输入和梯度幅度阈值相结合。第二种技术使用2D阈值,而第三种算法使用3D阈值。 MR图像用Kohonen自组织图对所有三种算法进行了分割。将这三种技术的Kappa值与每个观察者进行比较,并且在原始算法和第三种算法之间观察到统计学上的显着改进(观察者1:0.651、0.744,P = 0.015;观察者2:0.603、0.699,P = 0.024)。更加准确和可靠的定量分析减少了MR测量值的差异,并有助于临床试验以确定这一弱势人群的白质脑病的临床意义。

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