摘要
在早期癌症的发病表现中,肿块和微小钙化点是重要的特征和诊断依据。然而,病变可疑区域与正常组织区域之间的差别很小,并且肿块的边界和内部结构在超声图像上形态不一,与周围组织的差别也很细微,很难用人眼检查到,这样使得早期确诊变得比较困难。本文采用一种基于模糊数学理论的乳腺超声图像增强算法,经过增强处理之后,原先由于图像的模糊而隐藏的信息能够清晰的观察到,这也后后面的肿瘤的分割与分类打好基础。
In early cancer onset manifestation, masses and microcalcifications is important feature and diagnosis. However, lesions suspicious areas and normal tissue between the regional difference is very small, and the tumor boundary and internal structures in ultrasound image form, with the surrounding tissue differences also very subtle, very difficult to use eye examination, which makes early diagnosis difficult. In this paper, based on the theory of fuzzy mathematics the breast ultrasound image enhancement algorithm, enhanced by processing, originally due a fuzzy image and hidden information can be clearly observed, which also later behind the tumor segmentation and classification to lay a good foundation.
出处
《影像技术》
CAS
2012年第5期38-40,37,共4页
Image Technology
关键词
超声图像
图像增强算法.
Breast Ultrasound Image
Image Enhancement Algorithm
