This is a 3D visualization of how the Expectation
2016-08-23
0 0 0
no vote
Other
Earn points
Traditional single particle reconstruction methods use either the Fourier or the delta function basis to represent the particle density map. We propose a more flexible algorithm that adaptively chooses the basis based on the data. Because the basis adapts to the data, the reconstruction resolution and signal-to-noise ratio (SNR) is improved compared to a reconstruction with a fixed basis. Moreover, the algorithm automatically masks the particle, thereby separating it from the background. This eliminates the need for ad-hoc filtering or masking in the refinement loop. The algorithm is formulated in a Bayesian maximum-a-posteriori framework and uses an efficient optimization algorithm for the maximization. Evaluations using simulated and actual cryogenic electron microscopy data show resolution and SNR improvements as well as the effective masking of particle from background.
c
可视化
利用
算法
数据
混合
模型
Related Source Codes
PClite
0
0
no vote
generic embeded FTP Client
0
0
no vote
UDP Test Demo
0
0
no vote
TMS320F28335 DSP transmits data to EEPROM through
0
0
no vote
TMS320F28335 CAN communication source code
0
0
no vote
No comment