Image Analysis Training Resources: Glossary

Key Points

Tool installation
Digital image basics
Confocal microscopy image formation
Lookup tables
Spatial calibration
Data types
Image file formats
Big image data file formats
Slice viewing
Projections
Volume rendering
Segmentation
Thresholding
Automatic thresholding (histogram-based)
Connected component labeling
Object shape measurements
Nuclei segmentation and shape measurement
Object intensity measurements
Global background correction
Neighborhood filters
Median filter
Morphological filters
Local background correction
Object filtering
2D noisy object segmentation and filtering
Distance transform
Watershed
  • 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.

Skeletonization
Nuclei and cells segmentation
Segment Golgi objects per cell
Manual segmentation
Deep learning instance segmentation
Setting up a scripting environment
Running a script
Recording a script
Variables
Loops
Commenting
Working with strings
Output saving
Batch processing
Functions
Handling script parameters
Access S3 hosted OME-Zarr

Glossary

FIXME