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QI 2024 Analysis Lab Manual - Home
  • Welcome to QI 2024

Quantitative analysis labs

  • Estimating SNR & Resolution
  • Image Processing and Basic Segmentation
  • Image Correction and Intensity Measurements
  • Segmentation and Pixel Classification
  • Deep Learning for Microscopy Image Analysis
  • 3D Image Analysis
  • Image Time Series Analysis

Additional Resources

  • Helpful links for now and the future
  • Glossary
  • Bibliography
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Helpful links for now and the future

Contents

  • For finding experts to help you right now
  • Organizations that want to help
  • Places to learn more (or to learn where to learn more)
  • Blog posts you may like

Helpful links for now and the future#

For finding experts to help you right now#

  • forum.image.sc 17 - a centralized forum for >60 open source image analysis tools. Posts from beginners very welcome!

Organizations that want to help#

  • AI4Life

  • The Global Bioimage Analysts’ Society (GloBIAS)

Places to learn more (or to learn where to learn more)#

  • bioimagingguide.org 18

  • HMS CITE ‘favorite references’

  • Community-developed checklists for publishing images and image analyses 19

  • The Images to Knowledge conference

  • Metrics Reloaded 20,21,22 - an interactive tool for picking the right metric for measuring the accuracy of your imaging-related algorithm (segmentation, classification, etc)

  • Believing is seeing - the deceptive influence of bias in quantitative microscopy 23 - why even quantification is sometimes not enough to make sure your results are unbiased

Blog posts you may like#

  • How to write a bug report when your favorite software is broken

  • When to say ‘good enough’ in tuning your image analysis

  • Some best practices for beginners at Jupyter Notebook

  • “Thinking like an image analyst” blog series - going through the process of solving an image analysis problem. Parts: 1 2 3 4 5

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Image Time Series Analysis

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Glossary

Contents
  • For finding experts to help you right now
  • Organizations that want to help
  • Places to learn more (or to learn where to learn more)
  • Blog posts you may like

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