Study on CT Image Segmentation of Intracranial Hemorrhage
Based on Improved FCM Fuzzy Clustering
JIANG Chunyu1, LIU Jingxin2, ZHONG Huixiang1, LI Huiying1, LI Dajun3
1.College of Computer Science and Technology, Jilin University, Changchun Jilin 130012, China;
2.Department of Radiology, China-Japan Union Hospital of Jilin University, Changchun Jilin 130033, China;
3.Deparment of Gastroenterology, Jilin Province People’s Hospital, Changchun Jilin 130021, China
Abstract：In this paper, an improved fuzzy C-means (FCM) algorithm for the segmentation of intracranial hemorrhage lesions was
proposed for the hemorrhagic lesions of human brain CT images. Firstly, the brain CT images were pre-divided, and the intracranial
structures were extracted from the source CT images by left and right scanning algorithm and median filtering algorithm. Then the
pre-segmentation intracranial structures were obtained by adding the objective function and membership function to the spatial
information of improved FCM clustering algorithm for extraction of hemorrhagic lesions. Through CT brain images and CT brain
images with salt and pepper noise segmentation, the results showed that the algorithm was insensitive to noise and can accurately
segregate hemorrhagic lesions.
姜春雨1，刘景鑫2，钟慧湘1，李慧盈1，李大军3. 基于改进的FCM模糊聚类的颅内出血CT图像分割研究[J]. 中国医疗设备, 2018, 33(6): 16-20.
JIANG Chunyu1, LIU Jingxin2, ZHONG Huixiang1, LI Huiying1, LI Dajun3. Study on CT Image Segmentation of Intracranial Hemorrhage
Based on Improved FCM Fuzzy Clustering. China Medical Devices, 2018, 33(6): 16-20.
