Home
  • Code of Conduct
  • Setup
  • Modules
    • Automatic thresholding
    • Batch exploration of segmentation results
    • Big image data formats
    • Cloud based batch analysis
    • Cloud based interactive analysis
    • Connected component labeling
    • Convolutional filters
    • Correlative image rendering
    • Data types
    • Digital image basics
    • Distance transform
    • Fluorescence microscopy image formation
    • Global background correction
    • Image data formats
    • Local background correction
    • Lookup tables
    • Median filter
    • Morphological filters
    • Multichannel images
    • N-dimensional images
    • Neighborhood filters
    • Object filtering
    • Object intensity measurements
    • Object shape measurements
    • OME-TIFF
    • OME-Zarr
    • Projections
    • Segmentation overview
    • Skeletonization
    • Smart microscopy targeted imaging
    • Spatial calibration
    • Statistical (rank) filters
    • Thresholding
    • Tool installation
    • Volume rendering
    • Volume slicing
    • Watershed
    • Batch processing
    • Coding with LLMs
    • Functions
    • Loops
    • Output saving
    • Recording a script
    • Running a script
    • Strings and paths
    • Variables
    • Noisy object segmentation and filtering in 2D
    • Nuclei and cells segmentation
    • Nuclei segmentation and shape measurement
    • Quantitative image inspection and presentation
    • Bioimage tools containers
    • Deep learning instance segmentation
    • Image registration (DRAFT)
    • Manual segmentation
    • Remote (image) data access
    • Similarity transformations
    • Table file formats (DRAFT)
    • Template
    • Commenting
    • Fetching user input
    • Setting up a scripting environment
    • Cofilin rod formation (DRAFT)
    • Segment Golgi objects per cell
    • Module overview
  • Extras
    • Reference
    • About
    • Discussion
    • Figures
    • Instructor Notes
  • License
  • Improve this page

Automatic thresholding

Batch exploration of segmentation results

Big image data formats

Cloud based batch analysis

Cloud based interactive analysis

Connected component labeling

Convolutional filters

Correlative image rendering

Data types

Digital image basics

Distance transform

Fluorescence microscopy image formation

Global background correction

Image data formats

Local background correction

Lookup tables

Median filter

Morphological filters

Multichannel images

N-dimensional images

Neighborhood filters

Object filtering

Object intensity measurements

Object shape measurements

OME-TIFF

OME-Zarr

Projections

Segmentation overview

Skeletonization

Smart microscopy targeted imaging

Spatial calibration

Statistical (rank) filters

Thresholding

Tool installation

Volume rendering

Volume slicing

Watershed

Scripting: Batch processing

Scripting: Coding with LLMs

Scripting: Functions

Scripting: Loops

Scripting: Output saving

Scripting: Recording a script

Scripting: Running a script

Scripting: Strings and paths

Scripting: Variables

Workflow: Noisy object segmentation and filtering in 2D

Workflow: Nuclei and cells segmentation

Workflow: Nuclei segmentation and shape measurement

Workflow: Quantitative image inspection and presentation

Draft: Bioimage tools containers

Draft: Deep learning instance segmentation

Draft: Image registration (DRAFT)

Draft: Manual segmentation

Draft: Remote (image) data access

Draft: Similarity transformations

Draft: Table file formats (DRAFT)

Draft: Template

Draft: Commenting

Draft: Fetching user input

Draft: Setting up a scripting environment

Draft: Cofilin rod formation (DRAFT)

Draft: Segment Golgi objects per cell

Licensed under CC-BY 4.0 2019–2025 by NEUBIAS
Edit source file / Contributing / Source / Contact
Adapted from The Carpentries style version 9.5.3.