Tongde hospital of Zhejiang province, Zhejiang, 310012, Hangzhou, China.
J Med Syst. 2019 Jan 16;43(3):43. doi: 10.1007/s10916-019-1164-1.
Apparent diffusion coefficient (ADC), derived from diffusion-weighted magnetic resonance images (DW-MRI), measures the motion of water molecules in vivo and can be used to quantify tumor response so as to determine the best therapy approach. In this paper, our goal was to determine whether the DW-MRI can be used for qualitative and quantitative liver cancer analysis, where an automated method will be proposed for improving the accuracy of liver segmentation in DW-MRI to increase the ability of diagnosis of disease. We firstly analyzed the research status of liver cancer diagnosis, especially on the issues of liver image segmentation technology in MRI. Then, the imaging mechanism and image features of the DW-MRI were analyzed, and the initial DW-MRI slice was segmented by graph-cut algorithm. Finally, our obtained result from the liver DW-MRI image is quantitatively and qualitatively analyzed. Experimental results show that DW-MRI has a great advantage in the diagnosis, the DWI images of benign lesion group was lower than that of malignant lesion, thus DW-MRI is segmented by graph-cut algorithm can provide important additional information regarding differential diagnosis of specific liver cancer to some extend.
表观扩散系数（ADC）来源于扩散加权磁共振成像（DW-MRI），可测量体内水分子的运动，用于量化肿瘤反应，从而确定最佳治疗方法。本文旨在确定 DW-MRI 是否可用于定性和定量肝癌分析，提出一种自动方法以提高 DW-MRI 中肝脏分割的准确性，从而提高疾病诊断能力。我们首先分析了肝癌诊断的研究现状，特别是 MRI 中肝脏图像分割技术的问题。然后，分析了 DW-MRI 的成像机制和图像特征，并用图割算法对初始 DW-MRI 切片进行分割。最后，对肝脏 DW-MRI 图像进行了定量和定性分析。实验结果表明，DW-MRI 在诊断方面具有很大的优势，良性病变组的 DWI 图像低于恶性病变组，因此，通过图割算法对 DW-MRI 进行分割在一定程度上可以为特定肝癌的鉴别诊断提供重要的附加信息。
