摘要
目的通过抑制超声医学图像本身固有的斑纹噪声,改进超声图像分割的算法,使得超声分割的结果更加准确。方法采用基于重构形态学的分割算法,先对超声目标图像进行重构开运算与闭运算,再对开闭结果进行top-hat运算,提取出相应亮度或暗度特征,最后找出亮暗度特征的边界实现全自动分割。结果利用本文方法对超声心脏图象进行自动分割,结果图象中没有因噪声而产生的伪边界,能够准确反映心脏各腔的真实情况。结论本文方法能够实现对超声心脏图象各腔边界的完整提取,分割边界具有很好的连续性。此外,本文方法也可以对目标的明或暗特征单独提取,从而减小时间复杂度,并提高分割图象的准确性。
Objective To improve the precision of the traditional segmentation of echocardiogram, by suppressing the influence from inherent speckle noises in medical ultrasonic images. Method An automatic segmentation method based on reconstructed morphology was proposed in this paper.First, the opening and closing operations by reconstruction were imposed to the ultrasonic image.Second, the top-hat operation was used to extract the bright and/or dark features and to find out the boundaries corresponding to these features, whereby implemented the automatic segmentation. Result The segmented echocardiogram had less artificial boundaries resulted from speckle noise, and could accurately be extracted the artery and ventricle. Conclusion The presented method can detect both dark and bright objects accurately, and the boundary has a fine continuity. In addition, the algorithm is also applicable to the extraction of sole bright/dark features, accordingly to reduce the complexity and time needed and to improve the accuracv.
出处
《航天医学与医学工程》
CAS
CSCD
北大核心
2005年第4期246-250,共5页
Space Medicine & Medical Engineering
基金
National Science Foundation (60272060)
Doctoral Foundation of Ministry of Education (20030610032)
the Excellent Young Teachers Program of MOE(EYTP)
关键词
超生图像
形态学
重构
分割
超声心电描记术
ultrasonic images
morphology
reconstruction
segmentation
echocardiography
