Introduction to Image Analysis#

Overview#

This full-day course will introduce some of the fundamentals of image analysis using the popular open-source software - ImageJ.

The course is aimed at those new to image analysis, and no previous experience whatsoever is required

The only requirement is a laptop computer that you have admin access to. If you don’t have this, please get in contact prior to the course.

The focus will be on general image analysis principles which can be applied in any software package. Many of the example images will be from microscopy, but the principles are applicable to any imaging modality.

Aims#

  • Allow those new to microscopy to feel comfortable carrying out basic image analysis independently.

  • To provide a starting point for the more advanced image analysis methods that are becoming necessary in many areas of biomedical science.

Contents#

  • ImageJ/FIJI

  • Histograms, thresholding & segmentation

  • Smoothing & background subtraction

  • Morphological operators (erosion, dilation, opening, closing)

  • Watershed

  • Gradients & edge detection

  • Boolean algebra (AND, NOT, OR, XOR)

  • Deconvolution

  • Advanced segmentation using machine learning

  • Object measurement

  • ImageJ automation & macros

  • Experiment planning