At Ramona Optics, we love open source software! We believe open source tools can really empower users to move across different experiments, and create a common language for scientific exchange. After spending countless years with microscopy and biology experts, there is one free, open source image analysis software that stands out as nearly ubiquitous on a biologist’s desktop: ImageJ!

If you haven’t heard of ImageJ, it is a powerful scientific image analysis application written in Java that has enabled scientists to extract data from their images since 1995. To learn more about it, you can read on in here. In 2024, one of the most popular ways to get ImageJ installed on your system is with the Fiji distribution bundle. If you have to analyze, or even simply visualize microscopy data, we can definitely recommend it as a first tool to try!

To this effect, when we started to support the TIFF image file format, we emphasized compatibility with ImageJ as one of our priorities.

In this short post, we highlight a few key features of our Multi-Camera Array Microscope’s (MCAM®) compatibility with ImageJ and how you can use it as you start to make use of the MCAM to augment your previously established workflows.

Opening MCAM Hyperstacks in FIJI

When working with multi-dimensional image data, understanding the distinction between hyperstacks and normal stacks is crucial. A normal stack is a series of images that typically represent slices in one dimension, such as a stack through the height dimension of a sample, often referred to as a z-stack in a 3D image. In contrast, a hyperstack can encompass multiple dimensions simultaneously, including channels, slices (z), and frames (time).

In the context of an XYZC acquisition, the multi-channel acquisition mode on the MCAM, the image is organized with Z slices representing the T axis and the illumination channels representing the C axis. See an example of a multi-channel hyperstack from the MCAM below.

To open your multi-dimensional image in Fiji you have 2 options.

1. From the file explorer right click on the image file and click Open With… then select ImageJ

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2. From ImageJ navigate to File>Open… then select your file.

In the ImageJ interface, essential information about the loaded image is displayed in the information bar, located at the top of the window. Here, you can see details such as the selected channel index, time (T) or Z index, image label (often denoting the fluorescence channel used), pixel dimensions, bit depth, and file size in bytes. Below the image display area, scroll bars allow navigation through different channels and Z-index positions in the dataset. The main window provides a visual representation of the image, which in this example is displayed in 8-bit grayscale, a common format for fluorescence microscopy data. The central toolbar in the ImageJ main window offers quick access to essential functions for image analysis and adjustment, ensuring efficient workflow management for multi-dimensional imaging data.

Color Channels Representation in TIFF Files

When you open a TIFF file in Fiji that contains multiple color channels, each channel is typically represented as a separate image within the stack. The structure of the TIFF ensures that channel information is preserved, allowing Fiji to correctly interpret and display each channel.

For example, a TIFF with three color channels (Red, Green, Blue) will appear as a hyperstack with three channels. You can navigate between these channels using the channel dropdown menu or the channel slider located in the Fiji toolbar.

After navigating to Image > Color > Make Composite, ImageJ allows the user to visualize selected channels in an overlay format, providing a composite view that merges multiple channels into a single, color-coded image. This example includes an overlay of fluorescence channels acquired at 633nm and 380nm, showing both in their respective colors. Accessing the Image > Color > Channels Tool allows users to toggle individual channels within this composite.

The acquisition setup on the MCAM was to capture fluorescence 633nm, fluorescence 440nm, high-contrast brightfield, fluorescence 380nm, and fluorescence 530nm. Upon saving the acquisition on the MCAM a suggested lookup table for each channel is embedded in the image metadata for ImageJ to use. Here, only channels 633nm and 380nm are visualized, highlighting specific features while preserving the other channels for optional exploration or further analysis.

False Coloring and Re-labeling Color Channels

False coloring is a powerful technique to enhance the visualization of specific channels or features within your image. In Fiji, you can re-label or assign different colors to each channel to improve contrast or highlight particular structures.

To false color or re-label your color channels:

1. Select the Hyperstack: Ensure your image is loaded as a hyperstack with multiple channels.
2. Go to Image > Color > Channels Tool.
3. In the Channels Tool dialog, you can assign specific colors to each channel by selecting from the color dropdown menu next to each channel.
4. Alternatively, use Image > Lookup Tables to apply a predefined color map.
5. Click “OK” to apply the changes.

By customizing the color representation, you can make your data more interpretable and visually appealing.

Pixel Width, Length, and Area

Accurate measurement of spatial dimensions within your images is essential for quantitative analysis. Users frequently request information on how to measure pixel width, length, and area. Fiji provides robust tools to accomplish this by utilizing image metadata.

Pixel Width and Image Metadata

Pixel width refers to the real-world size that each pixel represents, often specified in micrometers (µm) or other units. This information is typically stored in the image metadata and is essential for converting pixel measurements to actual dimensions.

To read the pixel width and image metadata:

1. Open the Image: Load your image into Fiji.
2. Go to Analyze > Set Scale.
3. In the Set Scale dialog, Fiji will display the current pixel dimensions based on the metadata.
4. Ensure that the “Global” option is checked if you want to apply the scale to all images.
5. If the pixel dimensions are not correctly displayed, you can manually enter the scale based on your data acquisition settings.

Measuring a Drawn Line Using Pixel Width

Once the pixel width is set correctly, you can measure real-world distances within your image.

To measure the length of a drawn line:

1. Draw a Line: Use the line tool from the toolbar to draw a line between two points in your image.
2. Go to Analyze > Measure or press Ctrl+M.
3. The measurement results will include the length of the line in the units specified by the pixel width.

This allows for precise quantification of distances and other linear measurements within your images.

The MCAM provides the images, and ImageJ provides the means to dissect them! Despite the many tools our team at Ramona Optics have developed within our proprietary software for end-to-end data acquisition and integrated analysis, scientists will always have a need to push the boundaries of what is possible. Our integration with the toolkit provided by ImageJ and its open source community will be a critical component in image exploration for the full spectrum of research questions for years to come.

“Fiji: an open-source platform for biological-image analysis”. Schindelin et al. (2012). Nature Methods. DOI: 10.1038/nmeth.2019

To see more about our imaging and analysis solutions, visit ramonaoptics.com

This article was written by Clay Dugo, John Bechtel, Thomas “Jed” Doman, Natalie Alvarez, and Mark Harfouche, PhD.

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