Lines Detection: Use of the Radon Transform

 The classical approach to detect lines in an image is the Hough Transform. Here I'll present another alternative based on the Radon Transform (seen in my Learning Tomography series [see TOC]).

Python - Table of Contents

Section dedicated to Python and image manipulation

Playing with Phase and Magnitude

 

In this series dedicated to the Fourier Transform, it is important to understand the role played by magnitude (or amplitude) and phase in an image...

Model bias in cryo-EM - Einstein from noise

 

 
 
In the article of Maxim Shatsky et al.  entitled "A Method for the Alignment of Heterogeneous Macromolecules from Electron Microscopy" (J Struct Biol. 2009, 166(1): 67–78. doi:10.1016/j.jsb.2008.12.008.), the authors show that pure noise images aligned to a reference image give an average image resembling the reference. This is a perfect example of the model bias occurring during the 2D classification step. Let's do it!!!

Cryo-EM Table of Contents

Section dedicated to Cryo-Electron Microscopy and ImageJ

Case study: The target

In this case study, we want to count the number of points obtained in this shooting session.

Normal Map of a sphere using ImageJ

 A small script for creating a normal map of a sphere using ImageJ.