DiameterJ: A validated open source nanofiber diameter measurement tool

Abstract

Despite the growing use of nanofiber scaffolds for tissue engineering applications, there is not a validated, readily available, free solution for rapid, automated analysis of nanofiber diameter from scanning electron microscope (SEM) micrographs. Thus, the goal of this study was to create a user friendly ImageJ/FIJI plugin that would analyze SEM micrographs of nanofibers to determine nanofiber diameter on a desktop computer within 60 s. Additional design goals included 1) compatibility with a variety of existing segmentation algorithms, and 2) an open source code to enable further improvement of the plugin. Using existing algorithms for centerline determination, Euclidean distance transforms and a novel pixel transformation technique, a plugin called "DiameterJ" was created for ImageJ/FIJI. The plugin was validated using 1) digital synthetic images of white lines on a black background and 2) SEM images of nominally monodispersed steel wires of known diameters. DiameterJ analyzed SEM micrographs in 20 s, produced diameters not statistically different from known values, was over 10-times closer to known diameter values than other open source software, provided hundreds of times the sampling of manual measurement, and was hundreds of times faster than manual assessment of nanofiber diameter. DiameterJ enables users to rapidly and thoroughly determine the structural features of nanofiber scaffolds and could potentially allow new insights to be formed into fiber diameter distribution and cell response.

Keywords: FIJI; Image analysis; ImageJ; Morphology; Scaffold; Structure.

Figure 1

Diagram of fiber analysis algorithm. The starting input point is the black box labeled “Segmented Picture”. Grey Boxes are outputs of DiameterJ. Algorithms were not able to effectively determine fiber diameter at fiber intersections requiring subroutines to remove fiber intersections from the analysis leading to interconnected outputs within the code as indicated.

Figure 2

Analysis of calibration images to determine the mean line dia. Digital synthetic images were analyzed by DiameterJ (Super Pixel, Histogram) or BoneJ. Lines in (E) and (G), are colored by size (Blue>Red>Green) for ease of visual inspection but actual analysis was performed on images with white lines. The plot of the percent error between the diameter produced by the programs and the ground truth from the calibration images can be seen in Figures (B), (D), (F), and (H). The red dashed line represents 10 % error. N = 3 images for each data point in all graphs. Error bars were omitted for clarity.

Figure 3

DiameterJ Histogram algorithm peak fitting analysis to determine multi-modal line diameter distributions in Multi-Dia. calibration images. Lines in the digital synthetic images (A) are colored by size (Blue > Red > Green > Orange > Yellow > Purple) for visualization but analysis was performed on images with white fibers. (B) DiameterJ’s Histogram algorithm’s analysis of images in (A). Peak modes are indicated on histograms. (C) Gaussian peak fits for the “2 dia.” histogram in (B). The mean absolute error and percent error of the DiameterJ Histogram algorithm when Gaussian peaks are fit to each histogram in (D) and (E), respectively. Error bars represent standard error for N = 3 images.

Figure 4

Analysis of SEM micrographs of 316 stainless steel reference wire. (A, B) SEM micrographs of steel wire. (C) Optical image of 53 ga. steel wire. (D) DiameterJ’s Histogram algorithm output. Error in mean wire diameter of the single diameter (E), or mixed three diameter (F) steel wire micrographs for 5 different methodologies/algorithms. N= 6 images for all analyses. Error bars represent the standard deviation. Asterisks (*) indicate statistically different from DiameterJ’s Histogram algorithm; number signs (#) indicate statistical difference from human measure; plus signs (+) indicate statistical difference from DiameterJ’s Super Pixel algorithm; and an alpha sign (α) indicates statistical difference from PrC (P < 0.05).

Figure 5

Analysis of SEM micrographs of PLGA nanofibers. (A, B) SEM micrographs of PLGA nanofibers. (C, D) Cumulative fiber diameter histograms generated by DiameterJ Histogram (left) and by human measure (right). (E, F) Mean fiber diameter for different methodologies/algorithms. The mean and standard deviation in nm are given on the bars in (E). N = 6 images for all histograms and graphs. Error bars are standard deviation. Money sign ($) represents statistically different (P<0.1) from DiameterJ’s Histogram algorithm.

Figure 6

Segmentation algorithms and analysis of fiber dia., fiber orientation, mesh holes, porosity, intersection density and fiber length. (A) An SEM micrograph of 53 gauge wire (dia. 16.7 mm) was segmented with the indicated algorithms. Diameter (B) and Orientation (C) histograms produced by DiameterJ’s Histogram algorithm and OrientationJ given below their corresponding segmented images in (A). (D) Summary table of DiameterJ analysis of the segmented images. (E) Original SEM image of 53 ga. steel wire.