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Image Analysis 2 with Fiji
Ahmed E. Fetit, PhD4 May 2016
1Advanced Imaging Resource.
2
1. Quantitation Extracting numerical features out of your image
2. Co-localisation Spatial overlap between 2 labels
Why we are here - Quantification
SegmentationIdentify regions of interest
IdentifyMeasurements of interest
Identify Object of interest 1
Create a spatial mask
Identify objects of interest 2
Programme
• Recap – Analysis using ImageJ(Fiji)• Brightness & Contrast• Thresholding• Measuring • Analyse particles• Making selections
• Example use-cases• Quantify actin signal• Quantify nuclei of interest• Quantify foci• Compare nuclei to cytoplasm• Counting colonies
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• All settings need to be the same. Compare apples with apples.
• Sample preparation needs to be the same
• Microscope control needs to be the same in each. (*) Definitely for expression levels.
Before you start
Recap – Analysis using Fiji
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Bit-depth and dynamic range.
• Computer monitor is 8 bit -> Better visualisation.• Do conversion at the very end for publishing, etc.
256
65,536
Bit-depth and dynamic range.
Brightness and contrast.
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Thresholding.
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Measure thresholded regions.
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1. Set measurements 2. Measure
Analyse particles.
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Analyse Particles - Options
• Add to manager – Displays ROI manager with references to ROIs
• Summarise – Overall summary of measurements
• Display results – Measurement for each ROI
• Show options:
Overlay
Selections.
13Delete Edit -> Selection -> Select None.
Measure thresholded regionswithin selection.
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Example use-cases
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• Image -> cropDraw square
• Image• Colour • Split Channels
• Image• Adjust• Threshold
• Analyse -> Set measurement• Analyse -> Measure
• Quantify my actin (actin AF488) in a specific part of the eye (cornea)? • What do I tell ImageJ – Quantify green signal in user defined ROI?
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• Quantify nuclei using DAPI in a epicardium• What do I tell ImageJ – area of blue signal in specific ROI
• Image• Duplicate
• Image• Color• Split channel
• Draw polygon on original coloured image
• Edit• Selection• Restore selection
• Image• Adjust• Threshold
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Summary 1
Identify channel of interest – DAPI?Identify region of interest/ mask – use same or different channel to define it?Identify what needs to be quantified – area? Number of nuclei? Signal intensity?
Demo showed how ImageJ/Fiji can be used semi-automatically
For automating can use• ImageJ macros• Definiens large-scale
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• Quantify number of foci in nuclei (Colocalisation)• Quantify objects, identify channel, find maxima
• Image• Color• Split Channels
Select blue• Image• Adjust• Threshold
• Analyse• Particles(add to manager)
Select green• In ROI manager -> Show all
• Process• Find maxima
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Summary 2
Identify channel of interest – DAPI?Identify region of interest/ mask – use same or different channel to define it?Identify what needs to be quantified- FociWhat distinguishes Foci – in this case bright signal intensity?
Demo showed how ImageJ/Fiji can be used semi-automatically
For automating can use• ImageJ macros
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Quantify cytoplasm vs. nuclei
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Counting colonies (RGB image)
• Image• Color• Split channels
• Process• Binary• Make binary
• Place oval ROI• Process, Binary, Watershed
• Analyse Particles (100-2000 pixels)
Show: outlines
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Summary 3
RGB image – channel of interest is not so importantSegmenting overlapping objects is more importantIntensity can’t be used for segmentation
Demo showed how ImageJ/Fiji can be used semi-automatically
For automating can use• ImageJ macros
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Conclusion
• Identify clear aim for image analysis experiment
• Break down problem to manageable tasks: Identify channels, segmentation, identify objects
• Covered a number of scenarios:• Quantify actin signal• Quantify nuclei of interest• Quantify foci• Compare nuclei to cytoplasm• Counting colonies