Image Analysis Training Resources: Glossary

Key Points

Tool installation
Digital image basics
Lookup tables
  • A LUT has configurable contrast limits that determine the pixel value range that is rendered linearly.

  • LUT settings must be responsibly chosen to convey the intended scientific message and not to hide relevant information.

  • A gray scale LUT is usually preferable over a colour LUT, especially blue and red are not well visible for many people.

  • For high dynamic range images multi-color LUTs may be useful to visualise a wider range of pixel values.

Multichannel images
Spatial calibration
N-dimensional images
Data types
Image file formats
Quantitative image inspection and presentation
Volume slicing
Volume rendering
Automatic thresholding (histogram-based)
Connected component labeling
Object shape measurements
Nuclei segmentation and shape measurement
Fluorescence microscopy image formation
Object intensity measurements
Global background correction
Neighborhood filters
Median filter
2D noisy object segmentation and filtering
Morphological filters
Local background correction
Object filtering
Distance transform
  • A watershed transform can separate touching objects if there are intensity valleys (or ridges) between touching objects. In case of intensity ridges the image needs to be inverted before being subjected to the watershed transform.

  • To separate object by their shape, use a distance transform on the binary image and inject this into the watershed transform. It is often good to smooth the distance transform to remove spurious minima, which could serve as wrong seed points and thus lead to an over-segmentation.

Nuclei and cells segmentation
Similarity transformations
Running a script
Coding with LLMs
Recording a script
Working with strings
Output saving
Batch processing
Handling script parameters
Setting up a scripting environment
Correlative image rendering
Deep learning instance segmentation
Manual segmentation
Segment Golgi objects per cell
Big image data file formats