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引用本文:蒋秋霖,王 昕.基于电势能改进的区域生长脑肿瘤图像分割[J].软件工程,2018,21(8):1-3.【点击复制】
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基于电势能改进的区域生长脑肿瘤图像分割
蒋秋霖,王 昕
(长春工业大学计算机科学与工程学院,吉林 长春 130012)
摘 要: 脑肿瘤的图像分割被广泛应用于临床诊断中。为提高脑肿瘤分割的精确度,本文提出了一种结合电势能 的区域生长算法分割MR脑肿瘤图像。将图像的每个像素点看作是电荷,像素值作为电荷量,肿瘤区域像素值大因而其 “电荷量”大于其他非肿瘤区域“电荷量”,因此建立生长准则。实验对比其他两种典型算法,本文算法分割精度最优。
关键词: 脑肿瘤分割;电势能;区域生长
中图分类号: TP391.41    文献标识码: A
基金项目: 吉林省教育厅“十二五”科学技术研究项目(批准号:2014136).
Image Segmentation of Region Growing Brain Tumor Based on Potential Energy Segmentation
JIANG Qiulin,WANG Xin
( School of Computer Science & Engineering, Changchun University of Technology, Changchun 130012, China)
Abstract: Image segmentation of brain tumors is widely used in clinical diagnosis.In order to improve the accuracy of brain tumor segmentation,this paper proposes a region growing algorithm based on potential energy segmentation to segment MR brain tumor images.Each pixel of the image is regarded as a charge,and the pixel value is used as the charge amount. Since the tumor area has a larger pixel and thus its "charge amount" is larger than that of other non-tumor areas,a growth criterion is established.Compared two other typical algorithms,the proposed algorithm has the best segmentation accuracy
Keywords: brain tumor segmentation;electric potential energy;region growing


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