Microscopy Image Browser 2 (MIB2)

MIB2 is an update package for segmentation of multi-dimensional (2D-4D) microscopy datasets
2.1K Downloads
Updated 15 Mar 2024
With MIB2 you can analyse, segment and visualize various multidimensional datasets from both light and electron microscopy. MIB2 is completely rewritten to follow MVC architecture and brings additional stability among many new features.
See more further details and tutorials on MIB website: http://mib.helsinki.fi
I would like to acknowledge Matlab File Exchange user community and especially the authors whose functions were utilized during development of the program:
The MIB version 1 is available from here http://se.mathworks.com/matlabcentral/fileexchange/56481-microscopy-image-browser--mib- and recommended for Matlab version: R2011a - 2014a
List of all features with video tutorials is available from http://mib.helsinki.fi/features_all.html
Features:
  • Support 2D-4D datasets (x,y,c,z,t)
  • Up to 9 simultaneously opened datasets
  • Bounding box for each dataset
  • Extendible via plugins
  • Log of performed actions
  • Customizable undo system
  • Customizable keyboard shortcuts
  • Colorblind friendly color schemes
  • Regions of interests
  • Virtual stacking mode for working with datasets that are larger than available memory
  • Batch processing mode
Data import/export
  • Direct import/export with Matlab , Fiji , Imaris and system clipboard
  • Direct import from Omero server and URL links
  • Load and save to TIF, Amira Mesh, JPG, Fiji BigDataViewer, HDF5, MRC, NRRD, PNG formats
  • Load up to 100 different image and video formats
  • Microsoft Excel (export) for quantification
  • Rename and shuffle tool for unbiased classification and segmentation
Quantification and Statistics
  • Objects: Area (2D/3D)
  • Objects: ConvexArea (2D)
  • Objects: Curve Length (2D, pixels and image units)
  • Objects: Eccentricity (2D)
  • Objects: Equatorial Eccentricity (3D)
  • Objects: Equiv Diameter (2D)
  • Objects: Euler number (2D)
  • Objects: Extent (2D)
  • Objects: Filled area (2D/3D)
  • Objects: Holes area (2D/3D)
  • Objects: Length between end points (2D/3D)
  • Objects: Major axis length (2D/3D)
  • Objects: Meridional Eccentricity (3D)
  • Objects: Orientation (2D)
  • Objects: Perimeter (2D)
  • Objects: Second axis length (2D/3D)
  • Objects: Solidity (2D)
  • Objects: Third axis length (3D)
  • Intensity: Correlation (2D/3D)
  • Intensity: Maximal (2D/3D)
  • Intensity: Mean (2D/3D)
  • Intensity: Minimal (2D/3D)
  • Intensity: Standard deviation (2D/3D)
  • Intensity: Sum (2D/3D)
Measurements
  • Angles
  • Caliper
  • Circle, radius
  • Freehand distance and intensity profile
  • Linear distance and intensity profile
  • Polyline distance and intensity profile
  • Stereology
  • Wound healing assay
Segmentation tools
  • 3D ball (3D)
  • 3D lines (3D)
  • Annotations with values
  • Brush tool (2D)
  • Brush tool for 2D superpixels (SLIC , Watershed )
  • Black and White Thresholding tool (global, local, adaptive; 2D/3D)
  • Deep convolutional neural networks for train and prediction
  • Dilate (2D/3D, difference)
  • Drag & Drop
  • Erode (2D/3D, difference)
  • Fill holes (2D/3D)
  • Frame selection tool
  • Frangi tubular filter (2D/3D)
  • Graphcut based semi-automatic segmentation(2D/3D) ,
  • Lasso tool (2D/3D)
  • Magic Wand tool (2D/3D)
  • Membrane Click Tracker tool (2D/3D)
  • Morphological operations (branch points, diagonal fill, end points, skeleton, spur, thin, ultimate erosion)
  • Object Picker (2D/3D)
  • Quantification Filtering (2D/3D)
  • Random Forest Classifier (2D/3D)
  • Shape and Line Interpolation (3D)
  • Smooth (2D/3D)
  • Spot tool (2D/3D)
  • Watershed for automatic image segmentation and object separation (2D/3D)
Segmentation tools
  • 3D ball (3D)
  • 3D lines (3D)
  • Annotations with values
  • Brush tool (2D)
  • Brush tool for 2D superpixels (SLIC , Watershed )
  • Black and White Thresholding tool (global, local, adaptive; 2D/3D)
  • Deep convolutional neural networks for train and prediction
  • Dilate (2D/3D, difference)
  • Drag & Drop
  • Erode (2D/3D, difference)
  • Fill holes (2D/3D)
  • Frame selection tool
  • Frangi tubular filter (2D/3D)
  • Graphcut based semi-automatic segmentation(2D/3D) ,
  • Lasso tool (2D/3D)
  • Magic Wand tool (2D/3D)
  • Membrane Click Tracker tool (2D/3D)
  • Morphological operations (branch points, diagonal fill, end points, skeleton, spur, thin, ultimate erosion)
  • Object Picker (2D/3D)
  • Quantification Filtering (2D/3D)
  • Random Forest Classifier (2D/3D)
  • Shape and Line Interpolation (3D)
  • Smooth (2D/3D)
  • Spot tool (2D/3D)
  • Watershed for automatic image segmentation and object separation (2D/3D)
Image Processing
  • Add frame around the dataset
  • Alignment
  • Brightness, Contrast, Gamma adjustments
  • Chop and re-chop large dataset to smaller volumes
  • Content-aware fill
  • Contrast-limited adaptive histogram equalization
  • Color mode change (depth, color type)
  • Color channel operations (add, copy, delete, invert, rotate, shift, swap)
  • Crop , Resize , Flip , Rotate , Transpose
  • Crop 2D/3D objects to files
  • Debris removal
  • Image arithmetics
  • Image filters
  • Intensity normalization in Z/T (complete slice, masked areas, background shift)
  • Intensity replacement within selected areas
  • Invert
  • Manipulations with slices: insert, copy, delete
  • Intensity projections and focus stacking
  • Morphological operations
Visualization
  • Orthoslices (XY, ZX, ZY planes)
  • Volume Rendering (hardware)
  • Volume Rendering (software)
  • Models with Matlab isosurfaces
  • Models and volumes with Fiji 3D viewer
  • Models and volumes with Imaris
  • Export models to IMOD
  • Export models to Amira
  • Export models to 3D Slicer
  • Export models and volumes to Matlab Volume Viewer
  • Export models in STL format

Cite As

Ilya Belevich (2024). Microscopy Image Browser 2 (MIB2) (https://github.com/Ajaxels/MIB2), GitHub. Retrieved .

Belevich, Ilya, et al. “Microscopy Image Browser: A Platform for Segmentation and Analysis of Multidimensional Datasets.” PLOS Biology, vol. 14, no. 1, Public Library of Science (PLoS), Jan. 2016, p. e1002340, doi:10.1371/journal.pbio.1002340.

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Belevich, Ilya, and Eija Jokitalo. DeepMIB: User-Friendly and Open-Source Software for Training of Deep Learning Network for Biological Image Segmentation. Cold Spring Harbor Laboratory, July 2020, doi:10.1101/2020.07.13.200105.

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MATLAB Release Compatibility
Created with R2021a
Compatible with R2014b and later releases
Platform Compatibility
Windows macOS Linux

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Classes

Classes/@Labels

Classes/@Lines3D

Classes/@PoolWaitbar

Classes/@ToggleEventData

Classes/@mibAboutController

Classes/@mibAlignmentController

Classes/@mibAnnotationsController

Classes/@mibBatchController

Classes/@mibBoundingBoxController

Classes/@mibChildView

Classes/@mibChopDatasetController

Classes/@mibController

Classes/@mibCropController

Classes/@mibCropObjectsController

Classes/@mibDatasetInfoController

Classes/@mibDebrisRemovalController

Classes/@mibDeepController

Classes/@mibDragNDropControl

Classes/@mibExternalDirsController

Classes/@mibGraphcutController

Classes/@mibHistThresController

Classes/@mibImage

Classes/@mibImageAdjController

Classes/@mibImageArithmeticController

Classes/@mibImageFiltersController

Classes/@mibImageMorphOpsController

Classes/@mibImageSelectFrameController

Classes/@mibImageUndo

Classes/@mibImportOmeroController

Classes/@mibKeyShortcutsController

Classes/@mibLines3DController

Classes/@mibLogListController

Classes/@mibMakeMovieController

Classes/@mibMeasure

Classes/@mibMeasureToolController

Classes/@mibMembraneDetectionController

Classes/@mibModel

Classes/@mibMorphOpsController

Classes/@mibObjSepController

Classes/@mibPreferencesAppController

Classes/@mibPreferencesController

Classes/@mibRandomDatasetController

Classes/@mibRandomRestoreDatasetController

Classes/@mibRechopDatasetController

Classes/@mibResampleController

Classes/@mibRoiRegion

Classes/@mibSnapshotController

Classes/@mibStatisticsController

Classes/@mibStereologyController

Classes/@mibSupervoxelClassifierController

Classes/@mibTipsAppController

Classes/@mibTipsController

Classes/@mibUpdateCheckController

Classes/@mibView

Classes/@mibVolRenAppController

Classes/@mibVolRenAppViewerController

Classes/@mibVolRenController

Classes/@mibWatershedController

Classes/@mibWhiteBalanceController

Classes/@mibWoundHealingAssayController

Classes/@volrenAnimationController

Development/mibPluginGUI_ver1

Development/mibPluginGUI_ver2_Batch_compatible

Development/mibPluginGUI_ver3_appDesigner

Development/mibPlugin_withoutGUI

GuiTools

GuiTools/volren

ImportExportTools

ImportExportTools/Amira

ImportExportTools/BioFormats

ImportExportTools/BioFormats/private

ImportExportTools/Fiji

ImportExportTools/HDF5

ImportExportTools/IMOD

ImportExportTools/IMOD/@ImodChunk

ImportExportTools/IMOD/@ImodChunk/private

ImportExportTools/IMOD/@ImodContour

ImportExportTools/IMOD/@ImodContour/private

ImportExportTools/IMOD/@ImodMesh

ImportExportTools/IMOD/@ImodMesh/private

ImportExportTools/IMOD/@ImodModel

ImportExportTools/IMOD/@ImodModel/private

ImportExportTools/IMOD/@ImodObject

ImportExportTools/IMOD/@ImodObject/private

ImportExportTools/IMOD/@MRCImage

ImportExportTools/IMOD/@MRCImage/private

ImportExportTools/IMOD/Visualization

ImportExportTools/Imaris

ImportExportTools/Imaris/@IceImarisConnector

ImportExportTools/MatTomo/@ImodChunk

ImportExportTools/MatTomo/@ImodChunk/private

ImportExportTools/MatTomo/@ImodContour

ImportExportTools/MatTomo/@ImodContour/private

ImportExportTools/MatTomo/@ImodMesh

ImportExportTools/MatTomo/@ImodMesh/private

ImportExportTools/MatTomo/@ImodModel

ImportExportTools/MatTomo/@ImodModel/private

ImportExportTools/MatTomo/@ImodObject

ImportExportTools/MatTomo/@ImodObject/private

ImportExportTools/MatTomo/@MRCImage

ImportExportTools/MatTomo/@MRCImage/private

ImportExportTools/MatTomo/Utils

ImportExportTools/MatTomo/Visualization

ImportExportTools/Omero

ImportExportTools/export_fig

ImportExportTools/nrrd

Plugins/File Processing/ImageConverter

Plugins/IntensityAnalysis/TripleAreaIntensity

Plugins/MyPlugins/InterpolateObjects

Plugins/MyPlugins/mibAppDesignPlugin

Plugins/MyPlugins/mibPlugin

Plugins/MyPlugins/mibPluginWithoutGUI

Plugins/MyPlugins/myPluginName

Plugins/Organelle Analysis/MCcalc

Plugins/Organelle Analysis/SurfaceArea3D

Plugins/Organelle Analysis/ThreshAnalysisForObjects

Plugins/Plasmodesmata/CellWallThickness

Plugins/Plasmodesmata/SpacialControlPoints

Plugins/Tutorials/GuiTutorial

Tools

Tools/CellMigration

Tools/FastMarching

Tools/FastMarching/functions

Tools/FastMarching/shortestpath

Tools/Frangi

Tools/HistThresh

Tools/RandomForest/MembraneDetection

Tools/RandomForest/RF_Class_C

Tools/RandomForest/RF_Reg_C

Tools/RegionGrowing

Tools/Supervoxels

Tools/matGeom/geom2d

Tools/matGeom/geom3d

Tools/mibDeepSupport

Tools/prettify_MATLAB_html/publish overload

jars/xlwrite

techdoc

techdoc/prettify documentation

techdoc/publish overload

Plugins/IntensityAnalysis/TripleAreaIntensity

Plugins/Organelle Analysis/SurfaceArea3D

techdoc

techdoc/prettify documentation

Versions that use the GitHub default branch cannot be downloaded

Version Published Release Notes
2.8020

bug fixes:
fix of crash in compiled application when starting color chooser
fix when select directories dialog sends main MIB window to top
fix of ExternalDirectories in preferences initialization

2.8002

bug fix

2.8001

updated description

2.80

The update includes multiple improvements especially in training and segmentation of 2D convolutional neural networks with DeepMIB.
Full release notes: http://mib.helsinki.fi/downloads.html

2.70

- deep learning with DeepMIB to train deep convolutional networks for image segmentation
- 2D Elastic Distortion filter (Menu->Image->Image Filters)
- few other things...

2.60

Batch processing mode demo
Drag and Drop materials demo
Content-aware fill demo
Debris removal
and more
Batch processing mode
Drag and Drop materials
Content-aware fill
Debris removal
and more

2.1.0.0

added a demo image

To view or report issues in this GitHub add-on, visit the GitHub Repository.
To view or report issues in this GitHub add-on, visit the GitHub Repository.