摘要
检测和跟踪附着在神经元表面的量子的活动信息对于全面理解神经系统的工作机制具有重要意义。使用BIFs方法提取图像中的量子目标,并通过优化BIFs参数配置和融合高斯滤波预处理提高算法性能。实验结果表明该方法对强杂波干扰下的量子目标具有较高的检测率。
Detecting and tracking activities of the quantum dots which are attached on the surface of neurons helps to thoroughly understand how neural system works. We presented basic image features（BIFs） method to detect quantum dots in this paper. It also employed BIFs parameters optimization and a morphological filtering pre-processing to dexlude the clutters. Results show the methodology detect quantum dots of high clutters with high detection ratio.
出处
《微型机与应用》
2011年第16期34-35,共2页
Microcomputer & Its Applications
关键词
生物信息学
图像处理
形态学滤波
基本图像特征
bioinformatics
image processing
morphological filtering
basic image features
