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Computerized liver volumetry on MRI by using 3D geodesic active contour segmentation

机译:使用3D测地线主动轮廓分割进行MRI的计算机肝脏容量检查

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OBJECTIVE. Our purpose was to develop an accurate automated 3D liver segmentation scheme for measuring liver volumes on MRI. SUBJECTS AND METHODS. Our scheme for MRI liver volumetry consisted of three main stages. First, the preprocessing stage was applied to T1-weighted MRI of the liver in the portal venous phase to reduce noise and produce the boundary-enhanced image. This boundary-enhanced image was used as a speed function for a 3D fast-marching algorithm to generate an initial surface that roughly approximated the shape of the liver. A 3D geodesic-active-contour segmentation algorithm refined the initial surface to precisely determine the liver boundaries. The liver volumes determined by our scheme were compared with those manually traced by a radiologist, used as the reference standard. RESULTS. The two volumetric methods reached excellent agreement (intraclass correlation coefficient, 0.98) without statistical significance ( p = 0.42). The average (± SD) accuracy was 99.4% ± 0.14%, and the average Dice overlap coefficient was 93.6% ± 1.7%. The mean processing time for our automated scheme was 1.03 ± 0.13 minutes, whereas that for manual volumetry was 24.0 ± 4.4 minutes ( p < 0.001). CONCLUSION. The MRI liver volumetry based on our automated scheme agreed excellently with reference-standard volumetry, and it required substantially less completion time.
机译:目的。我们的目的是开发一种准确的自动化3D肝脏分割方案,以在MRI上测量肝脏体积。主题和方法。我们的MRI肝脏容量检查方案包括三个主要阶段。首先,将预处理阶段应用于门静脉期肝脏的T1加权MRI,以减少噪声并产生边界增强图像。该边界增强图像被用作3D快速行进算法的速度函数,以生成大致近似肝脏形状的初始表面。一种3D测地线-主动轮廓线分割算法可细化初始表面以精确确定肝脏边界。将通过我们的方案确定的肝脏体积与放射科医生手动追踪的肝脏体积进行比较,以用作参考标准。结果。两种体积方法达到了极好的一致性(类内相关系数为0.98),而无统计学意义(p = 0.42)。平均(±SD)准确度为99.4%±0.14%,平均Dice重叠系数为93.6%±1.7%。我们的自动化方案的平均处理时间为1.03±0.13分钟,而手动采样的平均处理时间为24.0±4.4分钟(p <0.001)。结论。基于我们的自动化方案的MRI肝脏容积测定仪与参考标准容积测定仪非常吻合,并且所需的完成时间大大减少。

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