一种用于从非增强T1加权磁共振图像中进行肾脏分割的半自动“整体”方法。
A semi-automated "blanket" method for renal segmentation from non-contrast T1-weighted MR images.
作者信息
Rusinek Henry, Lim Jeremy C, Wake Nicole, Seah Jas-mine, Botterill Elissa, Farquharson Shawna, Mikheev Artem, Lim Ruth P
机构信息
Center for Advanced Imaging Innovation and Research (CAI2R) and Department of Radiology, New York University School of Medicine, 660 1st Avenue, Rm413, New York, NY, 10016, USA.
Radiology, Austin Health, Melbourne, VIC, Australia.
出版信息
MAGMA. 2016 Apr;29(2):197-206. doi: 10.1007/s10334-015-0504-5. Epub 2015 Oct 29.
OBJECTIVE
To investigate the precision and accuracy of a new semi-automated method for kidney segmentation from single-breath-hold non-contrast MRI.
MATERIALS AND METHODS
The user draws approximate kidney contours on every tenth slice, focusing on separating adjacent organs from the kidney. The program then performs a sequence of fully automatic steps: contour filling, interpolation, non-uniformity correction, sampling of representative parenchyma signal, and 3D binary morphology. Three independent observers applied the method to images of 40 kidneys ranging in volume from 94.6 to 254.5 cm(3). Manually constructed reference masks were used to assess accuracy.
RESULTS
The volume errors for the three readers were: 4.4% ± 3.0%, 2.9% ± 2.3%, and 3.1% ± 2.7%. The relative discrepancy across readers was 2.5% ± 2.1%. The interactive processing time on average was 1.5 min per kidney.
CONCLUSIONS
Pending further validation, the semi-automated method could be applied for monitoring of renal status using non-contrast MRI.
目的
研究一种用于从单次屏气非增强磁共振成像（MRI）中进行肾脏分割的新型半自动方法的精度和准确性。
材料与方法
用户在每十层图像上绘制大致的肾脏轮廓，重点是将相邻器官与肾脏分开。然后程序执行一系列全自动步骤：轮廓填充、插值、不均匀性校正、代表性实质信号采样以及三维二值形态学处理。三名独立观察者将该方法应用于40个肾脏的图像，肾脏体积范围为94.6至254.5立方厘米。使用手动构建的参考掩码来评估准确性。
结果
三位读者的体积误差分别为：4.4%±3.0%、2.9%±2.3%和3.1%±2.7%。读者之间的相对差异为2.5%±2.1%。平均每个肾脏的交互式处理时间为1.5分钟。
结论
在进一步验证之前，该半自动方法可用于使用非增强MRI监测肾脏状态。
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