基于DoG掩模的冷冻电镜生物大分子图像特征提取

计算机科学 ›› 2010, Vol. 37 ›› Issue (9): 276-278.

基于DoG掩模的冷冻电镜生物大分子图像特征提取

巫小蓉,吴效明

(华南理工大学计算机科学与工程学院广州510641);(广东外语外贸大学信息科学技术学院广州510420);(华南理工大学生物工程学院广州510641)

出版日期:2018-12-01 发布日期:2018-12-01
基金资助:
本文受国家自然科学基金项目(30670538)，广东省高等院校学科建设专项资金资助.

Feature Extraction from Cryo-EM Image Based on DoG

WU Xiao-rong,WU Xiao-ming

Online:2018-12-01 Published:2018-12-01

摘要/Abstract

摘要： 针对冷冻电镜生物大分子图像低信噪比(SNR)和低对比度的特点，提出了基于高斯差分(DoG)掩模的形状特征提取方法。该方法利用高斯差分能提取多尺度梯度信号的优势，提取了目标生物大分子颗粒的近似区域，并在此基础上定义了由14个形状统计特征组成的特征向量。实验结果表明，该方法能有效提取生物大分子颗粒的形状特征，为进一步进行颗粒识别莫定了良好的基础。

关键词: 颗粒识别，大分子三维重构，高斯差分，形状特征，特征提取

Abstract: It may be difficult to extract distinctive features pertinent to a specimen when dealing with very low-contrast and low SNR cryo-Electron micrograph(Cryo-EM) images. A DoG(difference of Gaussian) based method to extract shape features was provided in this paper,which is aimed to get a binary image by using DoG. This binary image was used as an object mask and shape features were calculated for the largest object in the mask. The experiments showed this method has good results.

Key words: Particle picking, Macromolecular 3D reconstruction, DoG, Shape feature, Feature extraction

巫小蓉,吴效明. 基于DoG掩模的冷冻电镜生物大分子图像特征提取[J]. 计算机科学, 2010, 37(9): 276-278. https://doi.org/

WU Xiao-rong,WU Xiao-ming. Feature Extraction from Cryo-EM Image Based on DoG[J]. Computer Science, 2010, 37(9): 276-278. https://doi.org/

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