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FibrilTool, an ImageJ plug-in to quantify fibrillar structures in raw microscopy images


Cell biology heavily relies on the behavior of fibrillar structures, such as the cytoskeleton, yet the analysis of their behavior in tissues often remains qualitative. Image analysis tools have been developed to quantify this behavior, but they often involve an image pre-processing stage that may bias the output and/or they require specific software. Here we describe FibrilTool, an ImageJ plug-in based on the concept of nematic tensor, which can provide a quantitative description of the anisotropy of fiber arrays and their average orientation in cells, directly from raw images obtained by any form of microscopy. FibrilTool has been validated on microtubules, actin and cellulose microfibrils, but it may also help analyze other fibrillar structures, such as collagen, or the texture of various materials. The tool is ImageJ-based, and it is therefore freely accessible to the scientific community and does not require specific computational setup. The tool provides the average orientation and anisotropy of fiber arrays in a given region of interest (ROI) in a few seconds.

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Figure 1: Presentation of FibrilTool.
Figure 2: Effect of image quality and ROI selection on the FibrilTool output.
Figure 3: Test of FibrilTool on images with different types of fibrillar structures.


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This research was supported by a bilateral grant from Institut National de la Recherche Agronomique (INRA), France; by the Ministry of Science and Higher Education, Poland; by the MAESTRO research grant no. 2011/02/A/NZ3/00079 from the National Science Centre, Poland; and by a grant from Agence Nationale de la Recherche ANR-10-BLAN-1516 'Mechastem'. We thank Platim (UMS 3444 Biosciences Gerland-Lyon Sud) for help with imaging.

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Authors and Affiliations



The protocol was initiated and first tested by A. Boudaoud, M.U. and O.H. A. Boudaoud designed the ImageJ macros and supervised the formulation of the protocol. A. Burian, D.B.-W., R.W. and D.K. obtained images of fibrillar structures and used them to further test the macros. A. Boudaoud and O.H. wrote the manuscript with input from the other authors.

Corresponding author

Correspondence to Arezki Boudaoud.

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The authors declare no competing financial interests.

Integrated supplementary information

Supplementary Figure 1 Validation of FibrilTool with artificial images.

a-d. Examples of artificial images (372x372 pixels) obtained by generating 50 random segments (black segments, width 2 pixels) with (a,b) or with no (c,d) directional bias; the images in (a,c) were “degraded” by applying a Gaussian blur of radius 5 pixels (b,d); the theoretical orientation and anisotropy score can be computed directly from the distribution of segments, while the output of FibrilTool is shown in blue. e,f. Results of the analysis of a set of 10x3 such images with FibrilTool: raw images (continuous lines), moderately degraded images (blur of radius 3, dashed lines), and degraded images (blur of radius 5, dot-dashed lines). Data are plotted as a function of the theoretical anisotropy score: anisotropy score measured with FibrilTool (e); difference in degrees between orientation measured with FibrilTool and theoretical orientation (f).

Supplementary information

Supplementary Figure 1

Validation of FibrilTool with artificial images. (PDF 370 kb)

Supplementary Table 1

Sample excel file that can be used to copy-paste the contents of the Log file. (XLS 27 kb)

Supplementary Data 1

Source file of FibrilTool. (TXT 6 kb)

Supplementary Data 2

Source file of the DirectionPrinting macro. (TXT 0 kb)

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Boudaoud, A., Burian, A., Borowska-Wykręt, D. et al. FibrilTool, an ImageJ plug-in to quantify fibrillar structures in raw microscopy images. Nat Protoc 9, 457–463 (2014).

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