ModularImageAnalysis

Modular Image Analysis

A Fiji plugin providing a modular framework for assembling image and object analysis workflows

Extensive

Over 200 modules covering a wide range of image and object analysis processes such as transform, filtering, detection, measurement and visualisation

Input controlOutput controlSet intensity display rangeSet lookup tableSet spatial calibrationCreate 2D intensity histogramImage measurement calculatorMeasure Gini coefficientMeasure greyscale K-functionMeasure image colocalisationMeasure image dimensionsMeasure image intensityMeasure image intensity orientationMeasure image textureBinary operations (legacy)Binary operations 2DCalculate distance mapDilate and erodeExtended minima/maximaFill holesFill holes by volumeFix skeleton breaksSkeletoniseWatershed transformGlobal auto-thresholdLive manual thresholdLocal auto-thresholdManual thresholdThreshold imageApply CLAHEApply DeepImageJ modelBleaching correctionColour deconvolutionCombing correctionFilter imageImage calculatorImage mathImage type converterInvert image intensityManually edit imageNormalise intensityWeka pixel classificationWhite balance correctionAffine (MOPS)Affine (SIFT)Affine (block matching)Affine (fixed transform)Affine (manual)Affine (object centroids)Elastix registrationRegister imagesUnwarp (automatic)Unwarp (manual)Channel extractorConcatenate stacksConcatenate stacks 2Convert 3D stack (switch Z and T)Crop imageExtract substackFlip stackFocus stack (global)Focus stack (local)Interpolate Z axisMerge channelsProject imageReplace imageScale stackExport ACC datasetExport VOC annotationsExtract metadataLoad imageLoad image 2Load objectsLoad objects from ROIsSave imageSave image (generic)Save objects as ROIsSave overlay as ROIsConvert image to objectsConvert objects to imageCreate distance mapCellpose detectionCircle detectionCluster pointsCreate whole slice objectsIdentify objectsManually identify objectsRectangle detectionRidge detectionRun TrackMateSphere detectionSpot detectionStarDist detectionBased on measurementBased on metadataFilter objectsLive measurement filterMeasurement extremesNumber of childrenNumber of partnersObject proximityObjects with specific IDsRemove on image edgeWith / without measurementWith / without metadataWith / without parentMeasure intensity along pathMeasure object Gini coefficientMeasure object colocalisationMeasure object greyscale K-functionMeasure object intensityMeasure object intensity orientationMeasure object textureMeasure spot intensityMeasure texture along pathAdopt parent measurementAdopt parent metadataApply Weka object classificationBin objects by measurementCalculate statistics for childrenCalculate statistics for partnersChild object countObject measurement calculatorObject timepointParent object IDPartner object countReplace measurement valueCalculate nearest neighbourMeasure object centroidMeasure object curvatureMeasure object limitsMeasure object overlapMeasure object shapeMeasure object widthMeasure relative orientationMeasure specific widthMeasure track motionCreate bounding boxesCreate distance bandsCreate skeletonExtract object cross sectionExtract object edgesFit Gaussian 2DFit active contoursFit concave hull 2DFit convex hull 2DFit ellipseFit ellipsoidFit longest chordGet local object regionGet object surfaceGrow objectsCombine object setsMerge related objectsMerge single classObject slices to 3DRelate many-to-manyRelate many-to-oneRelate objectsRelate one-to-oneSingle class clusterKalman trackingOverlap tracking 3DTrack objectsDuplicate objectsDuplicate objects across timeExpand and shrink objectsFill holes in objectsInterpolate along ZMask objectsProject objectsReassign enclosed objectsResolve object overlapTrack editorRun macroRun macro on objectsRun scriptRun single commandAdd custom metadata itemGUI separatorGlobal variablesRemove imagesRemove objectsTest big imageAdd all object pointsAdd arrowsAdd contour linesAdd from position measurementAdd labelsAdd lineAdd object centroidAdd object fillAdd object outlineAdd overlayAdd relationship connectionAdd textAdd tracksClear overlayPlot measurement timeseriesPlot measurements as scatterPlot track motilityCreate measurement mapCreate orthogonal viewShow imageShow image measurementsShow metadataShow object measurementsShow object metadataAdd pauseFixed text conditionGUI conditionModule is enabled conditionWorkflow handling

Compatible

Designed with out-of-the-box support for spatially-calibrated 5D images, yielding image and object measurements in both pixel and physical units

Integrates with key ImageJ plugins such as Bio-Formats, TrackMate and Weka Trainable Segmentation

Efficient

MIA's modular design allows for efficient, automated, and high throughput image analysis

Automated

Workflows can be automated from initial image loading through processing, object detection, measurement extraction, visualisation, and data exporting

High throughput

Workflows are, by default, compatible with batch processing multiple files within a single folder

Memory Efficient

Dense spatial object data can be stored in a compressed quadtree coordinate structure to significantly reduce memory usage

Extensible

Functionality can be extended via integration with SciJava's scripting interface or with Java modules that extend the core MIA framework

1@Override
2public Status process(Workspace workspace) {
3    String inputObjectsName = parameters.getValue(INPUT_OBJECTS,workspace);
4    String outputObjectsName = parameters.getValue(OUTPUT_OBJECTS,workspace);
5
6    Objs inputObjects = workspace.getObjects().get(inputObjectsName);
7    SpatCal calIn = inputObjects.getSpatialCalibration();
8    SpatCal calOut = new SpatCal(calIn.getDppXY(), calIn.getDppZ(), calIn.getUnits(), calIn.getWidth(),
9            calIn.getHeight(), 1);
10    double frameInterval = inputObjects.getFrameInterval();
11    Unit<Time> temporalUnit = inputObjects.getTemporalUnit();
12    Objs outputObjects = new Objs(outputObjectsName, calOut, inputObjects.getNFrames(),
13            frameInterval, temporalUnit);
14
15    for (Obj inputObject:inputObjects.values()) {
16        try {
17            process(inputObject,outputObjects, true);
18        } catch (IntegerOverflowException e) {
19            return Status.FAIL;
20        }
21    }
22
23    workspace.addObjects(outputObjects);
24
25    // Showing objects
26    if (showOutput) outputObjects.convertToImageIDColours().show();
27
28    return Status.PASS;
29}

For you

Documented and ready to use for all your image analysis needs

Video Tutorials Guides Module Index