A Hybrid Method Based on Fuzzy C-Means Algorithm and Random Walker Algorithm
for CT Liver Image Segmentation
WANG Qinqin
Department of Radiology, Women’s Hospital of Nanjing Medical University, Nanjing Maternity and
Child Health Care Hospital, Nanjing Jiangsu 210004, China
Abstract:Objective To propose a hybrid segmentation method for liver tumors from CT imaging based on Fuzzy C-means (FCM) clustering algorithm with random walker algorithm. Methods The simulation images were selected from Midas and 3Dircadb databases. Firstly, the median filter was used for image preprocessing to smooth and keep the edge information of the image. Then, the CT liver image was initially divided into objects and background which has similar features by FCM method. Finally, random walker algorithm was adopted to draw the boundary of liver tumor for further segmentation. The accuracy ofimage segmentation resultsweremeasured by mean overlap error (OE), relative difference (RD), and Dice similarity coefficient (DSC). Results Qualitative analysisresults showed that the boundary of liver tumors was delineated accurately with the proposed method. Quantitative evaluation results showed that the image segmentation evaluation indexes obtained by using the segmentation algorithm of this study were superior to the algorithms reported in other literatures, and were consistent with the segmentation results of 5 experienced technicians. Moreover, the average overlap error rate, relative error and Dice similarity coefficient were 15.61%±5.32%, 4.02%±3.01%, 0.81±0.06, respectively. Conclusion The combination of FCM algorithm and random walk algorithm can segment CT liver tumor image accurately and effectively, which has high clinical application value.
王琴琴. 基于模糊C均值和随机漫步的CT肝脏图像分割算法研究[J]. 中国医疗设备, 2020, 35(9): 107-110.
WANG Qinqin. A Hybrid Method Based on Fuzzy C-Means Algorithm and Random Walker Algorithm
for CT Liver Image Segmentation. China Medical Devices, 2020, 35(9): 107-110.
Hong DJ,Zhu M,Zhu ZJ,et al.Clinical and muscle magnetic resonance image findings in patients with late-onset multiple acyl-CoA dehydrogenase deficiency[J].Chin Med J (Engl),2019,132(3):275-284.