Image Data Pop-Up Menu

Opens the Image Properties panel, in which the basic and advanced properties related to a dataset can be viewed and modified (see Image Properties Panel).

The following options are available to modify and transform image data.

Crop… Opens the Dataset Cropper panel, in which you can crop data to the bounding box defined with the Clip tool (see Cropping Datasets).

Sample… Opens the Dataset Sampler panel, in which you can modify image spacing by upsampling or downsampling (see Sampling Datasets).

Convert… Opens the Convert Dataset panel, in which you can restructure data according to different analysis needs (see Converting Image Data).

Resample Geometry… Copies the intersected values of the selected data into the geometry, or shape, of another object to create a new dataset (see Resampling Geometries).

Invert… Opens the Invert Dataset panel. In this panel you can invert the values and the X and Y axes of your image data, as well as apply an axis transformation (see Inverting Datasets).

Apply Transformation From… Applies transformations, such as translations, rotations, and scaling, that were applied to a reference object to the selected data (see Applying Transformations from Other Objects).

The following options are available to align objects.

With Current View… Automatically rotates image data so that the selected axis is aligned to the Z-axis of the world coordinate system, as shown below.

Centroid With… Automatically aligns the centroid of the selected data with the centroid of another object. Applicable objects include images, regions of interest, and multi-ROIs. You can choose the reference object in the Choose the Object to Align With dialog.

The following options are available for creating boxes that correspond to the geometry of the selected item or to the item's clip box.

Current Box… Opens the Create a Box dialog with the geometry set to the bounding box of the selected item.

Note You can edit the geometry before you create the box, as well as modify the Advanced Properties, such as the box's position in space.

Current Clip Box… Opens the Create a Box dialog with the geometry set to the clip box of the selected item.

Note You can edit the geometry before you create the box, as well as modify the Advanced Properties, such as the box's position in space.

Lets you to save reformations that were applied with the Translate/Rotate tool or by other methods. The result is a new dataset formatted in the current space (see Deriving New from Current View).

Lets you to save reformations that were applied with the Translate/Rotate tool or by other methods. The result is a new dataset with isotropic spacing formatted in the current space (see Deriving New from Current View).

Provides automated methods — Basic Otsu, Advanced Otsu, and Sobel Threshold — to reliably segment porosity (see Automated Porosity Segmentation).

The following options are available for exporting image data.

Images… Lets you export data to a number of different file formats (see Exporting Images).

As ORSObject… Exports data in the Dragonfly Object file (*.ORSObject extension) format (see Exporting Objects).

As DICOM… Exports data in the DICOM file format (see Exporting Images in the DICOM Format).

To VTK… Exports data in the VTK file format (*.vtk extension).

To CZI… Exports data in the CZI file format (*.czi extension). This option is available for Dragonfly 3D World ZEISS edition only. Contact Comet Technologies Canada Inc. for information about the availability of this version of Dragonfly.

Generates a contour mesh from data values above a selected threshold (see Generating Contour Meshes from Images).

Opens the Compare Histograms dialog, in which you can compare the histograms of multiple datasets (see Comparing Histograms).

Lets you apply deep learning regression models that you trained, imported, or downloaded for denoising and super resolution tasks to the selected data (see Filter with AI).

Lets you segment datasets with any of the deep learning or machine learning semantic segmentation models that you trained, imported, or downloaded (see Segment with AI).

Provides a shortcut for selecting macros that can be executed for the selected image data (see Recording and Playing Macros).

Opens the User Data dialog, in which you can view detailed object descriptions, as well as add fields to further describe the selected item (see Managing User Data).

Creates a multi-ROI in which each value in the dataset is assigned as a class. If there are 2,000 values in the dataset, then there will be 2,000 classes in the multi-ROI. Usually done after post-processing, such as creating a distance map, to create a sparse representation of the gray tones in a dataset. You should note that this option is not available for datasets in FLOAT and that values of 0 will not be assigned to a class.

Note In some cases, you may want to split non-connected labels that were created from the same data value (see Split Not Connected Labels).

Creates a distance map for a selected region of interest using Dijkstra's algorithm for finding the shortest paths between nodes.

Note Refer to en.wikipedia.org/wiki/Dijkstra%27s_algorithm for more information about Dijkstra's algorithm.

Creates a distance map for a selected region of interest using the numerical method created by James Sethian for solving boundary value problems of the Eikonal equation.

Note Refer to en.wikipedia.org/wiki/Fast_marching_method for more information about the fast marching method.

Creates a gridded multi-ROI in the same shape as the selected image data (see Making Gridded Multi-ROIs).

Lets you extract a new dataset from marked image slices (see Extracting New Images from Marked Slices).

Lets you create a 4D, or time-enabled, dataset from multiple datasets (see Creating 4D Images).

Lets you combine, or merge, multiple volumetric datasets into a single 3D dataset (see Stitch 3D Images).

Lets you to register a selected dataset to a baseline by modifying its position and/or rotation (see Image Registration).

Lets you create deformed or warped datasets. For example, to test invert problems such a non-rigid registration or to create additional data for deep model training (see 3D Data Augmentation).

Lets you to align the slices within a dataset to build a consistent image stack (see Aligning Image Stacks).

Lets you precisely combine, or stitch, overlapping 2D or 3D image tiles to create a single high-resolution image that is beyond the normal aspect ratio and resolution of a microscope's field of view (see Image Stitching).

Lets you create a new region of interest with the same shape as the selected image data and that is fully labeled within the selected range and increment (see Creating Mask ROIs).

Note Mask ROIs can used for training and applying Deep Learning and Classical Machine Learning models, computing Watersheds, and other computationally expensive tasks.

Automatically creates a new region of interest for each intensity value in the selected dataset.

Automatically computes the path linking two regions of interest (see Finding Paths Between ROIs).

Lets you normalize the histogram of the selected dataset to the histogram of a reference (see Normalizing Histograms).

Note This item will only be available if another dataset is loaded.

Lets you overwrite the values of an image with the intersecting values of a selected, or reference, image.

Note The reference image and the image to overwrite must be of the same data type — UBYTE, SHORT, UINT, or FLOAT. For best results, the image values should also be within the same range. If required, you can convert or normalize data within a selected range with the Image Converter (see Converting Image Data).

Do the following to overwrite image values:

1. Right-click the image you want to overwrite and then choose Overwrite with Another Image in the pop-up menu.
2. Choose the dataset you want to overwrite with in the Choose an Image to Overwrite With dialog.

   

3. Click OK.

Opens the Bone Analysis Wizard, which is designed for the evaluation of high-resolution micro-CTs of bone specimens (see Bone Analysis).

Opens the Plug Analysis Wizard, which provides a dedicated workflow for analyzing core plugs acquired from rock samples and other porous media.

Opens the Segmentation Wizard, which provides an easy-to-use, guided workflow for implementing powerful deep learning and classical machine learning segmentation of multi-dimensional images (see Segmentation Wizard).

Lets you evaluate and compare the image quality of previews and other 2D images with a number of different metrics, such as Sharpness, Shannon Entropy, SNR, and FactorQ (see Image Quality Metrics).

Lets you automatically update spacing and obtain the correct measurements for images, regions of interest, and multi-ROIs (see Spatial Scale Calibration).

Lets you calibrate the intensity scale of multiple images to a set of calibration standards (see Intensity Scale Calibration).

Extracts an object's history as a macro. Extracted macros not only provide an audit trail to help troubleshoot processing issues, but can be edited and replayed to create new objects (see Extracting Object Histories).

Can be used to remove small defects within an image or to replace lost or corrupted parts of image data (see Inpainting).

The following options are available to modify and transform image data.

Resample Geometries… Copies the intersected values of the selected data into the geometry, or shape, of another object (see Resampling Geometries).

The following options are available for exporting image data.

As Multiple ORSObject… Exports data as multiple files in the Dragonfly Object file (*.ORSObject extension) format (see Exporting Objects).

Export as ORSObject… Exports all data to a single file in the Dragonfly Object file (*.ORSObject extension) format (see Exporting Objects).

As RGB… Lets you export selected RGB channels in the BMP, JPEG, and PNG file formats (see Exporting Images as RGB).

To CZI… Exports data in the CZI file format (*.czi extension). This option is available for Dragonfly 3D World ZEISS edition only. Contact Comet Technologies Canada Inc. for information about the availability of this version of Dragonfly.

The following options are available to align objects.

With Current View… Automatically rotates image data so that the selected axis is aligned to the Z-axis of the world coordinate system.

Lets you apply deep learning regression models that you trained, imported, or downloaded for denoising and super resolution tasks to the selected data (see Filter with AI).

Lets you segment datasets with any of the deep learning or machine learning semantic segmentation models that you trained, imported, or downloaded (see Segment with AI).

Provides a shortcut for selecting macros that can be executed for the number of items selected.

Lets you create a 4D, or time-enabled, dataset from multiple images (see Creating 4D Images).

Lets you combine, or merge, multiple volumetric images into a single 3D dataset (see Stitch 3D Images).

Lets you normalize the histogram of the selected dataset to the histogram of a reference (see Normalizing Histograms).

Lets you generate images with scalar values of Phi and Theta orientations. You need to select at least two images to access this option and then choose the input datasets in the Choose Vector Field Component dialog.

Note You can use PuMA to compute the required X, Y, and Z images by selecting 'Orientation detection' as the computation type on the Solver tab (see Porous Microstructure Analysis (PuMA)).

Lets you create the following moment datasets from the current selection:

Mean… The first raw moment, which is the mean value of the pixels in the selection.

Variance… The second central moment.

Skewness… The third order moment about the mean. Skewness is a measure of symmetry, or more precisely, the lack of symmetry. A distribution, or dataset, is symmetric if it looks the same to the left and right of the center point.

Kurtosis… The fourth order moment about the mean. Kurtosis is a measure of whether data is heavy-tailed or light-tailed relative to a normal distribution. That is, datasets with high Kurtosis tend to have heavy tails, or outliers. Datasets with low Kurtosis tend to have light tails, or lack of outliers.

Hyperskewness… The fifth central moment.

Hyperflatness… The sixth central moment.

Lets you generate vector fields from datasets. For example, to further examine pressure and velocity data published from permeability simulations created in Dragonfly’s Porous Microstructure Analysis (PuMA) module.

Opens the Segmentation Wizard, which provides an easy-to-use, guided workflow for implementing powerful deep learning and classical machine learning segmentation of multi-dimensional images (see Segmentation Wizard).

Opens the Processed Image Comparator, in which you can evaluate the quality of processed image data with a number of metrics (see Processed Image Comparator).

Lets you automatically update spacing and obtain the correct measurements for images, regions of interest, and multi-ROIs (see Spatial Scale Calibration).