Workshop Description

Imaging datasets are becoming easier to acquire and more difficult to analyze. This workshop will provide an introduction to some of the computational tools available for manipulating images and extracting quantitative information from them. The main focus of this workshop will be on cellular imaging however much of the techniques are broadly applicable to other data types. We will cover image conversion and handling in python, different methods for normalizing, aligning and segmenting images and finally work on applying these techniques to a full image processing pipeline. The workshop will feature many hands-on exercises as well as some of the theory behind various key algorithms.

Day 1

Day 1:

  • Intro to digital image processing
  • Getting started with jupyter notebooks
    • Running notebooks and using the interface
  • Loading images into python
    • Different image types
    • Converting between types
    • Image formats
    • Using external libraries to load other data types
  • Manipulating arrays with numpy
  • Displaying images with matplotlib

Saving images

Day 2

Day 2:

  • Key aspects of an image processing pipeline
  • Introduction to scikit-Image
  • Normalization strategies
  • Convolution and fast Fourier transforms
  • Different types of filters
  • Edge detection
  • Segmentation
  • Image alignment and cross correlation

Day 3

Day 3

  • Applying techniques from day 1 and two to a full cell image processing pipeline.

Workshop Materials

The first 10 attendees can use the classroom computer, others can attend if using their own laptop. The room is equipped with ethernet jacks and wireless internet.

This workshop requires a working copy of Python3 (ideally 3.4 or later) with the below packages. If you are unable to install the packages on your own, please let me know before the class.

  • Numpy
  • SciKit-Image
  • Matplotlib
  • Jupyter Notebooks

The easiest way to install all of the above packages is to install the Anaconda distribution as they are all pre-installed. Make sure to choose the right distribution for your operating system.

If you prefer to set up your own python environment I recommend using a package manager like pip to install everything.


Marcus Gallagher-Jones, Ph.D., is a postdoctoral fellow working in the Rodriguez lab at UCLA. He received his BS in Biochemsitry from Durham University and his PhD in Biophysics from University of Liverpool before working for 2 years in the department of Physics at UCLA. His main interests are in structural analysis across many length-scales (atomic to whole cell) using electron and x-ray diffraction. His expertise include: structural biology, algorithm design, digital image processing, phase retrieval and tomographic reconstruction. Email:

Workshop Details

Prerequisites: TBA
Length: 3 days, 3 hrs per day
Level: Introductory
Location: Collaboratory Classroom  (Boyer Hall, 529)
Seats Available: 28

Spring 2019 Dates

Will return in Fall 2019.