Image Analysis Training Resources: Glossary

Key Points

Digital image basics
Thresholding
Morphological filters
Connected component labeling
Object shape measurements
Spatial calibration
N-dimensional images
Data types
Image data formats
Quantitative image inspection and presentation
Volume slicing
Big image data formats
Projections
Volume rendering
Segmentation
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
Local background correction
Object 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.

Nuclei and cells segmentation
Skeletonization
Similarity transformations
Running a script
Coding with LLMs
Recording a script
Variables
Strings and paths
Output saving
Batch processing
Handling input parameters
Commenting
Setting up a scripting environment
Functions
Loops
Correlative image rendering
Deep learning instance segmentation
Manual segmentation
Segment Golgi objects per cell

Glossary

FIXME