Directionality Plugin Imagej ((TOP)) Download

This plugin is used to infer the preferred orientation of structures present in the input image. It computes a histogram indicating the amount of structures in a given direction. Images with completely isotropic content are expected to give a flat histogram, whereas images in which there is a preferred orientation are expected to give a histogram with a peak at that orientation.

For instance, in the pine tree branch pictured above, the needle shaped leaves exist in 2 populations, one with a preferred orientation at about 45, and another one with preferred orientation around -45. This is well detected by the plugin, which reports two main peaks at 60 and -60. On top of that, a minor peak can be seen around 0, reporting the main branch orientation.

Directionality Plugin Imagej Download

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This plugin chops the image into square pieces, and computes their Fourier power spectra. The later are analyzed in polar coordinates, and the power is measured for each angle using the spatial filters proposed in 1.

Since version 2.0, the plugin offers the possibility to generate an orientation map, where the image is colored according to its local directionality, or location orientation. This has a well an easily defined meaning in the case of the local gradient orientation method, but things are a bit more complicated in the case of the Fourier component, which is a global method.

Since there is no publication associated with this plugin, it is hard tracking where it is used. However people wrote me and helped building the following list. The Directionality plugin has been used at least in the following publications:

We provide a software OrientationJ to produce to visualize and to measure the orientation in the images. This software package is a series of plugin running on ImageJ, Fiji, or ImageJ2a general purpose image-processing package. ImageJ has a public domain licence; it runs on several plateforms: Linux, Windows, Mac OSX.OrientationJ Analysis: Full interface to access to all features of the structure tensor and create color survey.OrientationJ Measure: Make measurement of the orientation and the coherency inside reion of interest.OrientationJ Distribution: Build a histogram of orientations based on selected structures.OrientationJ Corner Harris: Find corners in an image based the Harris corner detection.OrientationJ Vector Field: Evaluate the direction by regular patches.Test Image: Create a test image.Installation

We are trying to do a quantitative analysis of the pore direction with FIJI plugin (Directionality). We actually are not familiar with and never used FIJI/ImageJ before but we followed your instruction on and got the result (image below).

I have a question about installing the Directionality plugin. I downloaded the file on Github and followed the usual procedures to install it but unfortunately the java script would not compile to a .jar or .class. I have tried Compile and Run to no effect. The .java file is in my plugins folder and appears on the Plugins menu but only as a java script.

This plugin adds directionality controls to the toolbar, enabling TinyMCE to better handle languages written from right to left. It also adds a toolbar button for each of its values, ltr for left-to-right text and rtl for right-to-left text.

Now after a couple of days I am trying to use the Color Profiler plugin, which works perfectly fine when doing individual images, but when I use the same batch macro feature it gives me an Exception error for each image (I will attach the whole error). I tried doing it both in classical ImageJ and also the FIJI version, but it seems to give the same issue.

I can replicate the problem and it seems as if the plugin needs to actually display the image which is not the case with batch processing. I didn't investigate the source code of this rather old plugin, but here is an ImageJ-macro that should do what you want (with some flickering):

The tool uses the Directionality plugin to measure the main direction of the structures in the image and the dispersion. It is used in this context to analyze to which degree the muscles in the image are vertically aligned. The tool allows to run the Directionality plugin in batch-mode on a series of images. The direction-histograms and the measurements are exported as csv-files.

The tool stitches images from the Opera Phenix HCS System. It reads the Index.idx.xml file to pre-arrange the images and then stitches and fuses them using the Grid/Collection stitching-plugin. Images are stitched by plane and channel. Z-stacks and multi-channel images can optionally be created. Projections can also be create.

Formation of oriented myofibrils is a key event in musculoskeletal development. However, the mechanisms that drive myocyte orientation and fusion to control muscle directionality in adults remain enigmatic. Here, we demonstrate that the developing skeleton instructs the directional outgrowth of skeletal muscle and other soft tissues during limb and facial morphogenesis in zebrafish and mouse. Time-lapse live imaging reveals that during early craniofacial development, myoblasts condense into round clusters corresponding to future muscle groups. These clusters undergo oriented stretch and alignment during embryonic growth. Genetic perturbation of cartilage patterning or size disrupts the directionality and number of myofibrils in vivo. Laser ablation of musculoskeletal attachment points reveals tension imposed by cartilage expansion on the forming myofibers. Application of continuous tension using artificial attachment points, or stretchable membrane substrates, is sufficient to drive polarization of myocyte populations in vitro. Overall, this work outlines a biomechanical guidance mechanism that is potentially useful for engineering functional skeletal muscle.

Striated muscles do not form in isolation. They connect to skeletal elements or other structures starting from early developmental stages. Cartilage development precedes the bone4, and muscles initially attach to the cartilaginous templates of future skeletal elements5. Attachment of embryonic muscles to skeletal elements is mediated by specific cells, tenocytes, that express a set of markers that include Scleraxis (Scx) and Xirp26,7,8. Tenocytes diverge from common Sox9+ chondrogenic progenitors within immature mesenchymal condensations9. The particular positions of tenocytes might indeed have crucial importance in orienting the arriving myocytes, which will eventually form the muscle6. However, it is still not clear how tenocytes or emerging cartilages interact with forming muscles, and to what extent their interactions affect muscle size and directionality.

Similar to the in vivo situation with natural muscle attachment points, the pillar positions dictated the directionality of coalescing muscle tissue. We compared artificial tissues seeded with single (Fig. 6h), dual (Fig. 6i), and multiple attachment points (Fig. 6l). When we provided two attachment points, the individual myocytes were aligned along the pillar-to-pillar axis, and they formed a polarized and highly aligned muscle tissue, expressing -actinin, a muscle-specific structural protein (Fig. 6m, boxes 1 and 2). However, cell polarity was more uniform along the edges than in the very center, suggesting that the tissue edge might also influence cell polarity (Fig. 6m, compare boxes 2 and 3). When myoblasts were seeded without a second attachment point, cells attached to the single pillar also expressed -actinin (Fig. 6n upper), suggesting that attachment to a stiff object can induce differentiation. However, individual myotubes did not show directional consistency, and the overall tissue structure ended up in un-polarized aggregates (Fig. 6n lower). This result confirms that mechanical tension in a muscle cluster between two attachment points is sufficient to guide cell orientation.

Next, we looked into the cases of 3 or 4 attachment points (Fig. 6o, p). In these cases, myotubes near the pillar align following the axis pointing to the nearest pillar (Fig. 6o see boxes 1 and 3, and Fig. 6p, see box 1). Where most cells in the 2-pillar condition are either near a pillar or the tissue edge, 3-pillar and 4-pillar conditions feature large central regions of cells, distant from any directional input. Many cells positioned in these central areas of the tissue displayed random orientation, suggesting that increasing distance from attachment points, or distance from the tissue edges, reduces the effectiveness of directional cues for coherent cell orientation (Fig. 6o, p, inset windows 2). In these artificial 3D muscle tissues, polarization and orientation of individual muscle cells is entirely self-organized and only guided by the attachment points and the ensuing cell-generated mechanical tension that appears to primarily build along the tissue edges. These results show that mechanical tension is sufficient to drive directionality, elongation, and controlled fusion of individual muscle cells, but that this can be potentiated by muscle tissue shape.

Our results offer a resolution to a long-standing puzzle of how forming muscles acquire specific directionality and length. During embryonic development, muscle myofibrils attach to the cartilage before the bone forms66, which suggests the initiation of a functional interaction between cartilage and muscles at some point. However, it was not previously known whether the cartilage directs the development of muscle orientation. Consequently, the important biological question about how primary polarization of myocytes and final direction of myofibrils are established during development needed to be addressed. To answer this, we used live imaging and functional experiments in a zebrafish model system. We wanted to test the dependency of muscle orientation and other parameters on the position of progressively differentiating cartilaginous elements within the fish head. SOX9 and RUNX2 are key transcription factors directing cartilage differentiation30,31,67, and corresponding loss-of-function experiments led to severe cartilage fragmentation or disappearance. As a result, we observed misoriented and disorganized myofibrils in cranial muscles. Experimentally induced changes of the position of cartilage fragments in the head caused reorientation of the corresponding muscles. This led us to the conclusion that muscle size and directionality depend on the pattern of cartilaginous elements that myocytes can attach to. It remains an interesting question how muscles adaptively sense new attachment points after laser-induced cartilage destruction, as it might utilize mechanisms distinct from stereotypical attachment. Also noteworthy is that cartilage-dependent muscle polarization appears to be unique to craniofacial structures, as trunk myosepta develop without attaching to skeletal elements (Supplementary Movie 18). However, a basic principle of gradual displacement of attachment points, tension, and resulting cytoskeletal anisotropy driving cell shape changes is expected to apply in trunk muscle development as well. Whether other muscles (such as trunk myosepta) utilize such principles to set myocyte polarity will require further investigation. e24fc04721