Huynh Hieu Trung, Le-Trong Ngoc, Bao Pham The, Oto Aytek, Suzuki Kenji
Faculty of Information Technology, Industrial University of Ho Chi Minh City, Ho Chi Minh City, Vietnam.
Faculty of Information Technology, University of Science, Ho Chi Minh City, Vietnam.
Int J Comput Assist Radiol Surg. 2017 Feb;12(2):235-243. doi: 10.1007/s11548-016-1498-9. Epub 2016 Nov 21.
Our purpose is to develop a fully automated scheme for liver volume measurement in abdominal MR images, without requiring any user input or interaction.
The proposed scheme is fully automatic for liver volumetry from 3D abdominal MR images, and it consists of three main stages: preprocessing, rough liver shape generation, and liver extraction. The preprocessing stage reduced noise and enhanced the liver boundaries in 3D abdominal MR images. The rough liver shape was revealed fully automatically by using the watershed segmentation, thresholding transform, morphological operations, and statistical properties of the liver. An active contour model was applied to refine the rough liver shape to precisely obtain the liver boundaries. The liver volumes calculated by the proposed scheme were compared to the "gold standard" references which were estimated by an expert abdominal radiologist.
The liver volumes computed by using our developed scheme excellently agreed (Intra-class correlation coefficient was 0.94) with the "gold standard" manual volumes by the radiologist in the evaluation with 27 cases from multiple medical centers. The running time was 8.4 min per case on average.
We developed a fully automated liver volumetry scheme in MR, which does not require any interaction by users. It was evaluated with cases from multiple medical centers. The liver volumetry performance of our developed system was comparable to that of the gold standard manual volumetry, and it saved radiologists' time for manual liver volumetry of 24.7 min per case.
我们的目的是开发一种用于腹部磁共振成像中肝脏体积测量的全自动方案，无需任何用户输入或交互。
所提出的方案对于从三维腹部磁共振图像进行肝脏容积测量是完全自动的，它包括三个主要阶段：预处理、粗略肝脏形状生成和肝脏提取。预处理阶段减少了三维腹部磁共振图像中的噪声并增强了肝脏边界。通过使用分水岭分割、阈值变换、形态学操作以及肝脏的统计特性，完全自动地揭示了粗略的肝脏形状。应用主动轮廓模型来细化粗略的肝脏形状以精确获得肝脏边界。将所提出的方案计算出的肝脏体积与由腹部放射科专家估计的“金标准”参考值进行比较。
在对来自多个医疗中心的27例病例的评估中，使用我们开发的方案计算出的肝脏体积与放射科医生的“金标准”手动测量体积高度一致（组内相关系数为0.94）。平均每个病例的运行时间为8.4分钟。
我们开发了一种磁共振成像中的全自动肝脏容积测量方案，无需用户进行任何交互。对来自多个医疗中心的病例进行了评估。我们开发的系统的肝脏容积测量性能与金标准手动容积测量相当，并且为放射科医生节省了每个病例24.7分钟的手动肝脏容积测量时间。
