Table 1.

Mitochondrial morphology image analysis programs

	(Input parameters	Measurements	Analysis Platform	Validated on	Ref
	Computational classification of mitochondrial shape
	mito-GFP label; acquired with Leica DM16000 or Leica SP5 confocal microscope	Used random forest algorithm to classify mitochondria into blob, donut and elongated	MATLAB; Gemident	BEAS-2B, human primary bronchial epithelial cells, A549	[46]
	Computational imaging to use mitochondria as biomarker
	TOMM-20 immunostain; acquired with BX-63 upright automated fluorescence microscope equipped with 100x oil objective; z-stack 0.5μm; 2560 × 2160 pixel resolution. Used 2D image for analysis.	Used random forest algorithm to classify mitochondria into punctate, intermediate and filamentous	MATLAB	A2780, OVCA-429, A549, Caco-2, Panc- 1, H146, Jurkat, Daudi, patient derived xenograft samples	[47]
	Quantitative analysis of mitochondrial morphology using high content imaging, machine learning and morphological binning
	MitoTracker Deep Red label; acquired with wide-field fluorescence with offline deconvolution using GE InCell 2000 Analyzer; 40x 0.6 NA objective; pixel size 0.185μm; z-stack 1.55μm; used 3D image for analysis	Mitochondria defined in 4 subclasses (networked, rod-like, punctate, and large/round). Measured total mitochondrial area & object count, individual subclass area, average fiber length	GE INCel Developer Toolbox	661 w photoreceptor cells	[48]
	Multi-parametric analysis of mitochondria
	mito-GFP label; acquired with wide-field DeltaVision RT deconvolution microscope; 63X 1.40 NA oil objective, z-stack 0.22μm; used 2D image for analysis	Random Forest classifier using supervised classification model (separate into 3 classes: networked, fragmented, swollen)	Cell-Profiler software	MCF-7	[49]
	MicroP: automatic morphological subtyping
	MitoTracker Orange label; acquired with an Olympus fluorescence microscope (IX-71); 60× 1.45 NA objective; pixel (size 165nm, used 2D image for analysis	Total number/area of mitochondria. Classify mitochondria into subtypes: small globules, swollen globules, loops, straight tubules, twisted tubules, branched tubules.	MATLAB	CHO-K1	[50]
	Mitochondrial shape analysis with ImageJ
	mito-dsRED label; acquired with Fluoview 300 or 500 confocal 100x (1.3 NA)/60x objective (1.4 NA).	Area, major/minor axis of best fitting ellipse, aspect ratio, number ofmitochondria	FIJI	CV1	[43]
	TMRM labeled/Cytochrome c oxidase immunostain; acquired with LSM 510 LSCM or Leica epifluorescence microscope; used 2D image for analysis	Mitochondrial area, perimeter and major/minor axis of the bounding ellipse. Morphometric parameters: aspect ratio & form factor	FIJI	HeLa, PC12, hippocampal neurons	[42,51,52]
	Momito: novel algorithm to identify stress-induced alterations in mitochondrial connectivity
	TOM20 or mtHSP70 immunostain; acquired with Leica TSC SP8 confocal microscope; 63x/1.4 NA oil objective; used 2D image for analysis	Identifies mitochondrial tubules, junctions and endpoints. Measures mitochondrial length.	ImageJ & Momito algorithm	U2OS, WT and OPA1 KO	[53]
	MiNa: simple ImageJ macro to analyzing mitochondrial morphology
	mito-mEFP label; acquired on Carl Zeiss Axio Observer.Z1 inverted epifluorescence microscope; 63 × 1.4 NA oil objective; z-stack 0.25-0.3μm; used 2D image for analysis	Mitochondrial footprint, branch length (mean, median, standard deviation), number of branches (individual, networks, mean, median, standard deviation)	FIJI	SH-SY5Y, C2C12, MEF	[54]
	Mytoe: automatic analysis of mitochondrial dynamics
	mito-DsRED2 label; acquired on a Nikon Eclipse Ti with a Wallac-Perkin Ember Ultraview spinning disk confocal system 100x objective; used 3D image for analysis	Length, thickness, turtuosity, intensity, speed, direction, wiggle ratio, distance to centroid/nuclear membrane/cell membrane, orientation relative to x-axis/centroid, number of branches, total area, degree clustering, colocalization	PC stand alone application or MATLAB	U2OS	[55]
	MitoGraph: quantifying mitochondrial content
	mito-GFP/mitodsRed2 label; acquired on a Nikon Eclipse Ti chassis with a Yokogawa CSUX spinning-disk head; 100x 1.49 NA TIRF objective; 0.056 μm pixel size; Z-stack 0.2 μm; used 3D image for analysis	Total cell measurements (volume, total length, average width), individual mitochondrial measurements (nodes, edges, length), network characteristics	C++ program Visualization Toolkit (VTK))	S. cerevisae	[45,56]
	MitoMap: quantification of the mitochondrial network
	mito-LOC label; acquired with Deltavision 3D-SIM OMX system; 100× 1.4 NA oil objective; z-stack 0.125μm; used 3D image for analysis	Mean, sum, volume, surface area, compactness, distribution isotropy, isoperimetric quotient, sphericity, SA:V, radius variance	FIJI	S. cerevisae	[57]
	Mitochondrial morphological features associated with fission and fusion events
	mito-EYFP label; acquired with Nikon Ti Eclipse fluorescent microscope; 60x oil objective	Area, extent, solidity, perimeter, eccentricity and Euler number	MATLAB	U2OS	[58]
	Simultaneous quantitative measurement and automated analysis of mitochondrial morphology
	Rhodamine 123 label; acquired with a Nikon Diaphot inverted microscope; 40× 1.4 NA oil objective; image size 512×480 pixels	Area, perimeter, max/min radius, radius ration, max/min diameter, length, width, aspect ratio, form factor, number	Image Pro Plus 5.1	Healthy fibroblasts	[41]
	Multi-plexed high-content analysis of mitochondrial morphofunction
	TMRM labeled; acquired with a BD Pathway 855 system for automated wide field image acquisition equipped; 40× objective pixel size 210.5 μm × 160.4 μm	Aspect ratio, area, density, axis minor, diameter, radius, perimeter, roundness, length. width, count, box, feret, density and margination	Image Pro Plus & MATLAB	patient human skin fibroblasts	[59]
	Automated quantification and integrative analysis of 2D/3D mitochondria
	Mito-GFP label; acquired with LSM 510; 63x oil objective (1.40 NA); pixel size 0.0845 μm; z-step 0.364 μm; used 2D & 3D images for analysis	2D/3D shape analysis (count; area/volume; perimeter/surface area; formfactor/sphericity factor), 2D/3D network analysis (branch: count, points, length, diameter & volume); 2D/3D Network - Shape analysis	Image-Pro Plu software	HUVEC	[44]