Adiga P S Umesh, Malladi Ravi, Baxter William, Glaeser Robert M
Physical Biosciences Division, LBNL, 1, Cyclotron Road, Berkeley, CA 94720, USA.
J Struct Biol. 2004 Jan-Feb;145(1-2):142-51. doi: 10.1016/j.jsb.2003.10.026.
Three-dimensional reconstruction of ribosome particles from electron micrographs requires selection of many single-particle images. Roughly 100,000 particles are required to achieve approximately 10 A resolution. Manual selection of particles, by visual observation of the micrographs on a computer screen, is recognized as a bottleneck in automated single-particle reconstruction. This paper describes an efficient approach for automated boxing of ribosome particles in micrographs. Use of a fast, anisotropic non-linear reaction-diffusion method to pre-process micrographs and rank-leveling to enhance the contrast between particles and the background, followed by binary and morphological segmentation constitute the core of this technique. Modifying the shape of the particles to facilitate segmentation of individual particles within clusters and boxing the isolated particles is successfully attempted. Tests on a limited number of micrographs have shown that over 80% success is achieved in automatic particle picking.
从电子显微照片中对核糖体颗粒进行三维重建需要选择许多单颗粒图像。要达到约10埃的分辨率大约需要100,000个颗粒。通过在计算机屏幕上目视观察显微照片来手动选择颗粒，被认为是自动单颗粒重建中的一个瓶颈。本文描述了一种在显微照片中对核糖体颗粒进行自动框选的有效方法。使用快速各向异性非线性反应扩散方法对显微照片进行预处理并进行秩均衡以增强颗粒与背景之间的对比度，随后进行二值化和形态学分割构成了该技术的核心。成功尝试了修改颗粒形状以促进簇内单个颗粒的分割并对孤立颗粒进行框选。对有限数量的显微照片进行的测试表明，自动颗粒挑选的成功率超过80%。
